New work on denial of service in Tor will be presented at NDSS '14 on Tuesday, February 25th, 2014:
The Sniper Attack: Anonymously Deanonymizing and Disabling the Tor Network
by Rob Jansen, Florian Tschorsch, Aaron Johnson, and Björn Scheuermann
To appear at the 21st Symposium on Network and Distributed System Security
We found a new vulnerability in the design of Tor's flow control algorithm that can be exploited to remotely crash Tor relays. The attack is an extremely low resource attack in which an adversary's bandwidth may be traded for a target relay's memory (RAM) at an amplification rate of one to two orders of magnitude. Ironically, the adversary can use Tor to protect it's identity while attacking Tor without significantly reducing the effectiveness of the attack.
We studied relay availability under the attack using Shadow, a discrete-event network simulator that runs the real Tor software in a safe, private testing environment, and found that we could disable each of the fastest guard and the fastest exit relay in a range of 1-18 minutes (depending on relay RAM capacity). We also found that the entire group of the top 20 exit relays, representing roughly 35% of Tor bandwidth capacity at the time of the analysis, could be disabled in a range of 29 minutes to 3 hours and 50 minutes. We also analyzed how the attack could potentially be used to deanonymize hidden services, and found that it would take between 4 and 278 hours before the attack would succeed (again depending on relay RAM capacity, as well as the bandwidth resources used to launch the attack).
Due to our devastating findings, we also designed three defenses that mitigate our attacks, one of which provably renders the attack ineffective. Defenses have been implemented and deployed into the Tor software to ensure that the Tor network is no longer vulnerable as of Tor version 0.2.4.18-rc and later. Some of that work can be found in Trac tickets #9063, #9072, #9093, and #10169.
In the remainder of this post I will detail the attacks and defenses we analyzed, noting again that this information is presented more completely (and more elegantly) in our paper.
The Tor Network Infrastructure
The Tor network is a distributed system made up of thousands of computers running the Tor software that contribute their bandwidth, memory, and computational resources for the greater good. These machines are called Tor relays, because their main task is to forward or relay network traffic to another entity after performing some cryptographic operations. When a Tor user wants to download some data using Tor, the user's Tor client software will choose three relays from those available (an entry, middle, and exit), form a path or circuit between these relays, and then instruct the third relay (the exit) to fetch the data and send it back through the circuit. The data will get transferred from its source to the exit, from the exit to the middle, and from the middle to the entry before finally making its way to the client.
The client may request the exit to fetch large amounts of data, and so Tor uses a window-based flow control scheme in order to limit the amount of data each relay needs to buffer in memory at once. When a circuit is created, the exit will initialize its circuit package counter to 1000 cells, indicating that it is willing to send 1000 cells into the circuit. The exit decrements the package counter by one for every data cell it sends into the circuit (to the middle relay), and stops sending data when the package counter reaches 0. The client at the other end of the circuit keeps a delivery counter, and initializes it to 0 upon circuit creation. The client increments the delivery counter by 1 for every data cell it receives on that circuit. When the client's delivery counter reaches 100, it sends a special Tor control cell, called a SENDME cell, to the exit to signal that it received 100 cells. Upon receiving the SENDME, the exit adds 100 to its package counter and continues sending data into the circuit.
This flow control scheme limits the amount of outstanding data that may be in flight at any time (between the exit and the client) to 1000 cells, or about 500 KiB, per circuit. The same mechanism is used when data is flowing in the opposite direction (up from the client, through the entry and middle, and to the exit).
The Sniper Attack
The new Denial of Service (DoS) attack, which we call "The Sniper Attack", exploits the flow control algorithm to remotely crash a victim Tor relay by depleting its memory resources. The paper presents three attacks that rely on the following two techniques:
- the attacker stops reading from the TCP connection containing the attack circuit, which causes the TCP window on the victim's outgoing connection to close and the victim to buffer up to 1000 cells; and
- the attacker causes cells to be continuously sent to the victim (exceeding the 1000 cell limit and consuming the victim's memory resources) either by ignoring the package window at packaging end of the circuit, or by continuously sending SENDMEs from the delivery end to the packaging end even though no cells have been read by the delivery end.
Basic Version 1 (attacking an entry relay)
In basic version 1, the adversary controls the client and the exit relay, and chooses a victim for the entry relay position. The adversary builds a circuit through the victim to her own exit, and then the exit continuously generates and sends arbitrary data through the circuit toward the client while ignoring the package window limit. The client stops reading from the TCP connection to the entry relay, and the entry relay buffers all data being sent by the exit relay until it is killed by its OS out-of-memory killer.
Basic Version 2 (attacking an exit relay)
In basic version 2, the adversary controls the client and an Internet destination server (e.g. website), and chooses a victim for the exit relay position. The adversary builds a circuit through the victim exit relay, and then the client continuously generates and sends arbitrary data through the circuit toward the exit relay while ignoring the package window limit. The destination server stops reading from the TCP connection to the exit relay, and the exit relay buffers all data being sent by the client until it is killed by its OS out-of-memory killer.
Both of the basic versions of the attack above require the adversary to generate and send data, consuming roughly the same amount of upstream bandwidth as the victim's available memory. The efficient version reduces this cost by one to two orders of magnitude.
In the efficient version, the adversary controls only a client. She creates a circuit, choosing the victim for the entry position, and then instructs the exit relay to download a large file from some external Internet server. The client stops reading on the TCP connection to the entry relay, causing it to buffer 1000 cells.
At this point, the adversary may "trick" the exit relay into sending more cells by sending it a SENDME cell, even though the client has not actually received any cells from the entry. As long as this SENDME does not increase the exit relay's package counter to greater than 1000 cells, the exit relay will continue to package data from the server and send it into the circuit toward the victim. If the SENDME does cause the exit relay's package window to exceed the 1000 cell limit, it will stop responding on that circuit. However, the entry and middle node will hold the circuit open until the client issues another command, meaning its resources will not be freed.
The bandwidth cost of the attack after circuit creation is simply the bandwidth cost of occasionally sending a SENDME to the exit. The memory consumption speed depends on the bandwidth and congestion of non-victim circuit relays. We describe how to parallelize the attack using multiple circuits and multiple paths with diverse relays in order to draw upon Tor's inherent resources. We found that with roughly 50 KiB/s of upstream bandwidth, an attacker could consume the victim's memory at roughly 1 MiB/s. This is highly dependent on the victim's bandwidth capabilities: relays that use token buckets to restrict bandwidth usage will of course bound the attack's consumption rate.
Rather than connecting directly to the victim, the adversary may instead launch the attack through a separate Tor circuit using a second client instance and the "Socks4Proxy" or "Socks5Proxy" option. In this case, she may benefit from the anonymity that Tor itself provides in order to evade detection. We found that there is not a significant increase in bandwidth usage when anonymizing the attack in this way.
A simple but naive defense against the Sniper Attack is to have the guard node watch its queue length, and if it ever fills to over 1000 cells, kill the circuit. This defense does not prevent the adversary from parallelizing the attack by using multiple circuits (and then consuming 1000 cells on each), which we have shown to be extremely effective.
Another defense, called "authenticated SENDMEs", tries to protect against receiving a SENDME from a node that didn't actually receive 100 cells. In this approach, a 1 byte nonce is placed in every 100th cell by the packaging end, and that nonce must be included by the delivery end in the SENDME (otherwise the packaging end rejects the SENDME as inauthentic). As above, this does not protect against the parallel attack. It also doesn't defend against either of the basic attacks where the adversary controls the packaging end and ignores the SENDMEs anyway.
The best defense, as we suggested to the Tor developers, is to implement a custom, adaptive out-of-memory circuit killer in application space (i.e. inside Tor). The circuit killer is only activated when memory becomes scarce, and then it chooses the circuit with the oldest front-most cell in its circuit queue. This will prevent the Sniper Attack by killing off all of the attack circuits.
With this new defense in place, the next game is for the adversary to try to cause Tor to kill an honest circuit. In order for an adversary to cause an honest circuit to get killed, it must ensure that the front-most cell on its malicious circuit queue is at least slightly "younger" than the oldest cell on any honest queue. We show that the Sniper Attack is impractical with this defense: due to fairness mechanisms in Tor, the adversary must spend an extraordinary amount of bandwidth keeping its cells young — bandwidth that would likely be better served in a more traditional brute-force DoS attack.
Tor has implemented a version of the out-of-memory killer for circuits, and is currently working on expanding this to channel and connection buffers as well.
Hidden Service Attack and Countermeasures
The paper also shows how the Sniper Attack can be used to deanonymize hidden services:
- run a malicious entry guard relay;
- run the attack from Oakland 2013 to learn the current guard relay of the target hidden service;
- run the Sniper Attack on the guard from step 2, knocking it offline and causing the hidden service to choose a new guard;
- repeat, until the hidden service chooses the relay from step 1 as its new entry guard.
The technique to verify that the hidden service is using a malicious guard in step 4 is the same technique used in step 2.
In the paper, we compute the expected time to succeed in this attack while running malicious relays of various capacities. It takes longer to succeed against relays that have more RAM, since it relies on the Sniper Attack to consume enough RAM to kill the relay (which itself depends on the bandwidth capacity of the victim relay). For the malicious relay bandwidth capacities and honest relay RAM amounts used in their estimate, we found that deanonymization would involve between 18 and 132 Sniper Attacks and take between ~4 and ~278 hours.
This attack becomes much more difficult if the relay is rebooted soon after it crashes, and the attack is ineffective when Tor relays are properly defending against the Sniper Attack (see the "Defenses" section above).
Strategies to defend hidden services in particular go beyond those suggested here to include entry guard rate-limiting, where you stop building circuits if you notice that your new guards keep going down (failing closed), and middle guards, guard nodes for your guard nodes. Both of these strategies attempt to make it harder to coerce the hidden service into building new circuits or exposing itself to new relays, since that is precisely what is needed for deanonymization.
The main defense implemented in Tor will start killing circuits when memory gets low. Currently, Tor uses a configuration option (MaxMemInCellQueues) that allows a relay operator to configure when the circuit-killer should be activated. There is likely not one single value that makes sense here: if it is too high, then relays with lower memory will not be protected; if it is too low, then there may be more false positives resulting in honest circuits being killed. Can Tor determine this setting in an OS-independent way that allows relays to automatically find the right value for MaxMemInCellQueues?
The defenses against the Sniper Attack prevent the adversary from crashing the victim relay, but the adversary may still consume a relay's bandwidth (and memory resources, to a critical level) at relatively low cost. This means that even though the Sniper Attack can no longer kill a relay, it can still consume a large amount of its bandwidth at a relatively low cost (similar to more traditional bandwidth amplification attacks). More analysis of general bandwidth consumption attacks and defenses remains a useful research problem.
Finally, hidden services also need some love. More work is needed to redesign them in a way that does not allow a client to cause the hidden service to choose new relays on demand.
There are tensions in the Tor protocol design between the anonymity provided by entry guards and the performance improvements from better load balancing. This blog post walks through the research questions I raised in 2011, then summarizes answers from three recent papers written by researchers in the Tor community, and finishes by explaining what Tor design changes we need to make to provide better anonymity, and what we'll be trading off.
Part one: The research questions
In Tor, each client selects a few relays at random, and chooses only from those relays when making the first hop of each circuit. This entry guard design helps in three ways:
First, entry guards protect against the "predecessor attack": if Alice (the user) instead chose new relays for each circuit, eventually an attacker who runs a few relays would be her first and last hop. With entry guards, the risk of end-to-end correlation for any given circuit is the same, but the cumulative risk for all her circuits over time is capped.
Second, they help to protect against the "denial of service as denial of anonymity" attack, where an attacker who runs quite a few relays fails any circuit that he's a part of and that he can't win against, forcing Alice to generate more circuits and thus increasing the overall chance that the attacker wins. Entry guards greatly reduce the risk, since Alice will never choose outside of a few nodes for her first hop.
Third, entry guards raise the startup cost to an adversary who runs relays in order to trace users. Without entry guards, the attacker can sign up some relays and immediately start having chances to observe Alice's circuits. With them, new adversarial relays won't have the Guard flag so won't be chosen as the first hop of any circuit; and even once they earn the Guard flag, users who have already chosen guards won't switch away from their current guards for quite a while.
In August 2011, I posted these four open research questions around guard rotation parameters:
- Natural churn: For an adversary that controls a given number of relays, if the user only replaces her guards when the current ones become unavailable, how long will it take until she's picked an adversary's guard?
- Artificial churn: How much more risk does she introduce by intentionally switching to new guards before she has to, to load balance better?
- Number of guards: What are the tradeoffs in performance and anonymity from picking three guards vs two or one? By default Tor picks three guards, since if we picked only one then some clients would pick a slow one and be sad forever. On the other hand, picking only one makes users safer.
- Better Guard flag assignment: If we give the Guard flag to more or different relays, how much does it change all these answers?
For reference, Tor 0.2.3's entry guard behavior is "choose three guards, adding another one if two of those three go down but going back to the original ones if they come back up, and also throw out (aka rotate) a guard 4-8 weeks after you chose it." I'll discuss in "Part three" of this post what changes we should make to improve this policy.
Part two: Recent research papers
Tariq Elahi, a grad student in Ian Goldberg's group in Waterloo, began to answer the above research questions in his paper Changing of the Guards: A Framework for Understanding and Improving Entry Guard Selection in Tor (published at WPES 2012). His paper used eight months of real-world historical Tor network data (from April 2011 to December 2011) and simulated various guard rotation policies to see which approaches protect users better.
Tariq's paper considered a quite small adversary: he let all the clients pick honest guards, and then added one new small guard to the 800 or so existing guards. The question is then what fraction of clients use this new guard over time. Here's a graph from the paper, showing (assuming all users pick three guards) the vulnerability due to natural churn ("without guard rotation") vs natural churn plus also intentional guard rotation:
In this graph their tiny guard node, in the "without guard rotation" scenario, ends up getting used by about 3% of the clients in the first few months, and gets up to 10% by the eight-month mark. The more risky scenario — which Tor uses today — sees the risk shoot up to 14% in the first few months. (Note that the y-axis in the graph only goes up to 16%, mostly because the attacking guard is so small.)
The second paper to raise the issue is from Alex Biryukov, Ivan Pustogarov, and Ralf-Philipp Weinmann in Luxembourg. Their paper Trawling for Tor Hidden Services: Detection, Measurement, Deanonymization (published at Oakland 2013) mostly focuses on other attacks (like how to censor or track popularity of hidden services), but their Section VI.C. talks about the "run a relay and wait until the client picks you as her guard" attack. In this case they run the numbers for a much larger adversary: if they run 13.8% of the Tor network for eight months there's more than a 90% chance of a given hidden service using their guard sometime during that period. That's a huge fraction of the network, but it's also a huge chance of success. And since hidden services in this case are basically the same as Tor clients (they choose guards and build circuits the same way), it's reasonable to conclude that their attack works against normal clients too so long as the clients use Tor often enough during that time.
I should clarify three points here.
First clarifying point: Tariq's paper makes two simplifying assumptions when calling an attack successful if the adversary's relay *ever* gets into the user's guard set. 1) He assumes that the adversary is also either watching the user's destination (e.g. the website she's going to), or he's running enough exit relays that he'll for sure be able to see the correponding flow out of the Tor network. 2) He assumes that the end-to-end correlation attack (matching up the incoming flow to the outgoing flow) is instantaneous and perfect. Alex's paper argues pretty convincingly that these two assumptions are easier to make in the case of attacking a hidden service (since the adversary can dictate how often the hidden service makes a new circuit, as well as what the traffic pattern looks like), and the paper I describe next addresses the first assumption, but the second one ("how successful is the correlation attack at scale?" or maybe better, "how do the false positives in the correlation attack compare to the false negatives?") remains an open research question.
Researchers generally agree that given a handful of traffic flows, it's easy to match them up. But what about the millions of traffic flows we have now? What levels of false positives (algorithm says "match!" when it's wrong) are acceptable to this attacker? Are there some simple, not too burdensome, tricks we can do to drive up the false positives rates, even if we all agree that those tricks wouldn't work in the "just looking at a handful of flows" case?
More precisely, it's possible that correlation attacks don't scale well because as the number of Tor clients grows, the chance that the exit stream actually came from a different Tor client (not the one you're watching) grows. So the confidence in your match needs to grow along with that or your false positive rate will explode. The people who say that correlation attacks don't scale use phrases like "say your correlation attack is 99.9% accurate" when arguing it. The folks who think it does scale use phrases like "I can easily make my correlation attack arbitrarily accurate." My hope is that the reality is somewhere in between — correlation attacks in the current Tor network can probably be made plenty accurate, but perhaps with some simple design changes we can improve the situation. In any case, I'm not going to try to tackle that research question here, except to point out that 1) it's actually unclear in practice whether you're done with the attack if you get your relay into the user's guard set, or if you are now faced with a challenging flow correlation problem that could produce false positives, and 2) the goal of the entry guard design is to make this issue moot: it sure would be nice to have a design where it's hard for adversaries to get into a position to see both sides, since it would make it irrelevant how good they are at traffic correlation.
Second clarifying point: it's about the probabilities, and that's intentional. Some people might be scared by phrases like "there's an x% chance over y months to be able to get an attacker's relay into the user's guard set." After all, they reason, shouldn't Tor provide absolute anonymity rather than probabilistic anonymity? This point is even trickier in the face of centralized anonymity services that promise "100% guaranteed" anonymity, when what they really mean is "we could watch everything you do, and we might sell or give up your data in some cases, and even if we don't there's still just one point on the network where an eavesdropper can learn everything." Tor's path selection strategy distributes trust over multiple relays to avoid this centralization. The trouble here isn't that there's a chance for the adversary to win — the trouble is that our current parameters make that chance bigger than it needs to be.
To make it even clearer: the entry guard design is doing its job here, just not well enough. Specifically, *without* using the entry guard design, an adversary who runs some relays would very quickly find himself as the first hop of one of the user's circuits.
Third clarifying point: we're considering an attacker who wants to learn if the user *ever* goes to a given destination. There are plenty of reasonable other things an attacker might be trying to learn, like building a profile of many or all of the user's destinations, but in this case Tariq's paper counts a successful attack as one that confirms (subject to the above assumptions) that the user visited a given destination once.
And that brings us to the third paper, by Aaron Johnson et al: Users Get Routed: Traffic Correlation on Tor by Realistic Adversaries (upcoming at CCS 2013). This paper ties together two previous series of research papers: the first is "what if the attacker runs a relay?" which is what the above two papers talked about, and the second is "what if the attacker can watch part of the Internet?"
The first part of the paper should sound pretty familiar by now: they simulated running a few entry guards that together make up 10% of the guard capacity in the Tor network, and they showed that (again using historical Tor network data, but this time from October 2012 to March 2013) the chance that the user has made a circuit using the adversary's relays is more than 80% by the six month mark.
In this case their simulation includes the adversary running a fast exit relay too, and the user performs a set of sessions over time. They observe that the user's traffic passes over pretty much all the exit relays (which makes sense since Tor doesn't use an "exit guard" design). Or summarizing at an even higher level, the conclusion is that so long as the user uses Tor enough, this paper confirms the findings in the earlier two papers.
Where it gets interesting is when they explain that "the adversary could run a relay" is not the only risk to worry about. They build on the series of papers started by "Location Diversity in Anonymity Networks" (WPES 2004), "AS-awareness in Tor path selection" (CCS 2009), and most recently "An Empirical Evaluation of Relay Selection in Tor" (NDSS 2013). These papers look at the chance that traffic from a given Tor circuit will traverse a given set of Internet links.
Their point, which like all good ideas is obvious in retrospect, is that rather than running a guard relay and waiting for the user to switch to it, the attacker should instead monitor as many Internet links as he can, and wait for the user to use a guard such that traffic between the user and the guard passes over one of the links the adversary is watching.
This part of the paper raises as many questions as it answers. In particular, all the users they considered are in or near Germany. There are also quite a few Tor relays in Germany. How much of their results here can be explained by pecularities of Internet connectivity in Germany? Are their results predictive in any way about how users on other continents would fare? Or said another way, how can we learn whether their conclusion shouldn't instead be "German Tor users are screwed, because look how Germany's Internet topology is set up"? Secondly, their scenario has the adversary control the Autonomous System (AS) or Internet Exchange Point (IXP) that maximally deanonymizes the user (they exclude the AS that contains the user and the AS that contains her destinations). This "best possible point to attack" assumption a) doesn't consider how hard it is to compromise that particular part of the Internet, and b) seems like it will often be part of the Internet topology near the user (and thus vary greatly depending on which user you're looking at). And third, like the previous papers, they think of an AS as a single Internet location that the adversary is either monitoring or not monitoring. Some ASes, like large telecoms, are quite big and spread out.
That said, I think it's clear from this paper that there *do* exist realistic scenarios where Tor users are at high risk from an adversary watching the nearby Internet infrastructure and/or parts of the Internet backbone. Changing the guard rotation parameters as I describe in "Part three" below will help in some of these cases but probably won't help in all of them. The canonical example that I've given in talks about "a person in Syria using Tor to visit a website in Syria" remains a very serious worry.
The paper also makes me think about exit traffic patterns, and how to better protect people who use Tor for only a short period of time: many websites pull in resources from all over, especially resources from centralized ad sites. This risk (that it greatly speeds the rate at which an adversary watching a few exit points — or heck, a few ad sites — will be able to observe a given user's exit traffic) provides the most compelling reason I've heard so far to ship Tor Browser Bundle with an ad blocker — or maybe better, with something like Request Policy that doesn't even touch the sites in the first place. On the other hand, Mike Perry still doesn't want to ship an ad blocker in TBB, since he doesn't want to pick a fight with Google and give them even more of a reason to block/drop all Tor traffic. I can see that perspective too.
Part three: How to fix it
Here are five steps we should take, in rough order of how much impact I think each of them would have on the above attacks.
If you like metaphors, think of each time you pick a new guard as a coin flip (heads you get the adversary's guard, tails you're safe this time), and the ideas here aim to reduce both the number and frequency of coin flips.
Fix 1: Tor clients should use fewer guards.
The primary benefit to moving to fewer guards is that there are fewer coin flips every time you pick your guards.
But there's a second benefit as well: right now your choice of guards acts as a kind of fingerprint for you, since very few other users will have picked the same three guards you did. (This fingerprint is only usable by an attacker who can discover your guard list, but in some scenarios that's a realistic attack.) To be more concrete: if the adversary learns that you have a particular three guards, and later sees an anonymous user with exactly the same guards, how likely is it to be you? Moving to two guards helps the math a lot here, since you'll overlap with many more users when everybody is only picking two.
On the other hand, the main downside is increased variation in performance. Here's Figure 10 from Tariq's paper:
"Farther to the right" is better in this graph. When you pick three guards (the red line), the average speed of your guards is pretty good (and pretty predictable), since most guards are pretty fast and it's unlikely you'll pick slow ones for all three. However, when you only pick only one guard (the purple line), the odds go up a lot that you get unlucky and pick a slow one. In more concrete numbers, half of the Tor users will see up to 60% worse performance.
The fix of course is to raise the bar for becoming a guard, so every possible guard will be acceptably fast. But then we have fewer guards total, increasing the vulnerability from other attacks! Finding the right balance (as many guards as possible, but all of them fast) is going to be an ongoing challenge. See Brainstorm tradeoffs from moving to 2 (or even 1) guards (ticket 9273) for more discussion.
Switching to just one guard will also preclude deploying Conflux, a recent proposal to improve Tor performance by routing traffic over multiple paths in parallel. The Conflux design is appealing because it not only lets us make better use of lower-bandwidth relays (which we'll need to do if we want to greatly grow the size of the Tor network), but it also lets us dynamically adapt to congestion by shifting traffic to less congested routes. Maybe some sort of "guard family" idea can work, where a single coin flip chooses a pair of guards and then we split our traffic over them. But if we want to avoid doubling the exposure to a network-level adversary, we might want to make sure that these two guards are near each other on the network — I think the analysis of the network-level adversary in Aaron's paper is the strongest argument for restricting the variety of Internet paths that traffic takes between the Tor client and the Tor network.
This discussion about reducing the number of guards also relates to bridges: right now if you configure ten bridges, you round-robin over all of them. It seems wise for us to instead use only the first bridge in our bridge list, to cut down on the set of Internet-level adversaries that get to see the traffic flows going into the Tor network.
Fix 2: Tor clients should keep their guards for longer.
In addition to choosing fewer guards, we should also avoid switching guards so often. I originally picked "one or two months" for guard rotation since it seemed like a very long time. In Tor 0.2.4, we've changed it to "two or three months". But I think changing the guard rotation period to a year or more is probably much wiser, since it will slow down the curves on all the graphs in the above research papers.
I asked Aaron to make a graph comparing the success of an attacker who runs 10% of the guard capacity, in the "choose 3 guards and rotate them every 1-2 months" case and the "choose 1 guard and never rotate" case:
In the "3 guard" case (the blue line), the attacker's success rate rapidly grows to about 25%, and then it steadily grows to over 80% by the six month mark. The "1 guard" case (green line), on the other hand, grows to 10% (which makes sense since the adversary runs 10% of the guards), but then it levels off and grows only slowly as a function of network churn. By the six month mark, even this very large adversary's success rate is still under 25%.
So the good news is that by choosing better guard rotation parameters, we can almost entirely resolve the vulnerabilities described in these three papers. Great!
Or to phrase it more as a research question, once we get rid of this known issue, I'm curious how the new graphs over time will look, especially when we have a more sophisticated analysis of the "network observer" adversary. I bet there are some neat other attacks that we'll need to explore and resolve, but that are being masked by the poor guard parameter issue.
However, fixing the guard rotation period issue is alas not as simple as we might hope. The fundamental problem has to do with "load balancing": allocating traffic onto the Tor network so each relay is used the right amount. If Tor clients choose a guard and stick with it for a year or more, then old guards (relays that have been around and stable for a long time) will see a lot of use, and new guards will see very little use.
I wrote a separate blog post to provide background for this issue: "The lifecycle of a new relay". Imagine if the ramp-up period in the graph from that blog post were a year long! People would set up fast relays, they would get the Guard flag, and suddenly they'd see little to no traffic for months. We'd be throwing away easily half of the capacity volunteered by relays.
One approach to resolving the conflict would be for the directory authorities to track how much of the past n months each relay has had the Guard flag, and publish a fraction in the networkstatus consensus. Then we'd teach clients to rebalance their path selection choices so a relay that's been a Guard for only half of the past year only counts 50% as a guard in terms of using that relay in other positions in circuits. See Load balance right when we have higher guard rotation periods (ticket 9321) for more discussion, and see Raise our guard rotation period (ticket 8240) for earlier discussions.
Yet another challenge here is that sticking to the same guard for a year gives plenty of time for an attacker to identify the guard and attack it somehow. It's particularly easy to identify the guard(s) for hidden services currently (since as mentioned above, the adversary can control the rate at which hidden services make new circuits, simply by visiting the hidden service), but similar attacks can probably be made to work against normal Tor clients — see e.g. the http-level refresh tricks in How Much Anonymity does Network Latency Leak? This attack would effectively turn Tor into a network of one-hop proxies, to an attacker who can efficiently enumerate guards. That's not a complete attack, but it sure does make me nervous.
One possible direction for a fix is to a) isolate streams by browser tab, so all the requests from a given browser tab go to the same circuit, but different browser tabs get different circuits, and then b) stick to the same three-hop circuit (i.e. same guard, middle, and exit) for the lifetime of that session (browser tab). How to slow down guard enumeration attacks is a tough and complex topic, and it's too broad for this blog post, but I raise the issue here as a reminder of how interconnected anonymity attacks and defenses are. See Slow Guard Discovery of Hidden Services and Clients (ticket 9001) for more discussion.
Fix 3: The Tor code should better handle edge cases where you can't reach your guard briefly.
If a temporary network hiccup makes your guard unreachable, you switch to another one. But how long is it until you switch back? If the adversary's goal is to learn whether you ever go to a target website, then even a brief switch to a guard that the adversary can control or observe could be enough to mess up your anonymity.
Tor clients fetch a new networkstatus consensus every 2-4 hours, and they are willing to retry non-running guards if the new consensus says they're up again.
But I think there are a series of little bugs and edge cases where the Tor client abandons a guard more quickly than it should. For example, we mark a guard as failed if any of our circuit requests time out before finishing the handshake with the first hop. We should audit both the design and the source code with an eye towards identifying and resolving these issues.
We should also consider whether an adversary can *induce* congestion or resource exhaustion to cause a target user to switch away from her guard. Such an attack could work very nicely coupled with the guard enumeration attacks discussed above.
Most of these problems exist because in the early days we emphasized reachability ("make sure Tor works") over anonymity ("be very sure that your guard is gone before you try another one"). How should we handle this tradeoff between availability and anonymity: should you simply stop working if you've switched guards too many times recently? I imagine different users would choose different answers to that tradeoff, depending on their priorities. It sounds like we should make it easier for users to select "preserve my anonymity even if it means lower availability". But at the same time, we should remember the lessons from Anonymity Loves Company: Usability and the Network Effect about how letting users choose different settings can make them more distinguishable.
Fix 4: We need to make the network bigger.
We've been working hard in recent years to get more relay capacity. The result is a more than four-fold increase in network capacity since 2011:
As the network grows, an attacker with a given set of resources will have less success at the attacks described in this blog post. To put some numbers on it, while the relay adversary in Aaron's paper (who carries 660mbit/s of Tor traffic) represented 10% of the guard capacity in October 2012, that very same attacker would have been 20% of the guard capacity in October 2011. Today that attacker is about 5% of the guard capacity. Growing the size of the network translates directly into better defense against these attacks.
However, the analysis is more complex when it comes to a network adversary. Just adding more relays (and more relay capacity) doesn't always help. For example, adding more relay capacity in a part of the network that the adversary is already observing can actually *decrease* anonymity, because it increases the fraction the adversary can watch. We discussed many of these issues in the thread about turning funding into more exit relays. For more details about the relay distribution in the current Tor network, check out Compass, our tool to explore what fraction of relay capacity is run in each country or AS. Also check out Lunar's relay bubble graphs.
Yet another open research question in the field of anonymous communications is how the success rate of a network adversary changes as the Tor network changes. If we were to plot the success rate of the *relay* adversary using historical Tor network data over time, it's pretty clear that the success rate would be going down over time as the network grows. But what's the trend for the success rate of the network adversary over the past few years? Nobody knows. It could be going up or down. And even if it is going down, it could be going down quickly or slowly.
(Read more in Research problem: measuring the safety of the Tor network where I describe some of these issues in more detail.)
Recent papers have gone through enormous effort to get one, very approximate, snapshot of the Internet's topology. Doing that effort retroactively and over long and dynamic time periods seems even more difficult and more likely to introduce errors.
It may be that the realities of Internet topology centralization make it so that there are fundamental limits on how much safety Tor users can have in a given network location. On the other hand, researchers like Aaron Johnson are optimistic that "network topology aware" path selection can improve Tor's protection against this style of attack. Much work remains.
Fix 5: We should assign the guard flag more intelligently.
In point 1 above I talked about why we need to raise the bar for becoming a guard, so all guards can provide adequate bandwidth. On the other hand, having fewer guards is directly at odds with point 4 above.
My original guard rotation parameters blog post ends with this question: what algorithm should we use to assign Guard flags such that a) we assign the flag to as many relays as possible, yet b) we minimize the chance that Alice will use the adversary's node as a guard?
We should use historical Tor network data to pick good values for the parameters that decide which relays become guards. This remains a great thesis topic if somebody wants to pick it up.
Part four: Other thoughts
What does all of this discussion mean for the rest of Tor? I'll close by trying to tie this blog post to the broader Tor world.
First, all three of these papers come from the Tor research community, and it's great that Tor gets such attention. We get this attention because we put so much effort into making it easy for researchers to analyze Tor: we've worked closely with these authors to help them understand Tor and focus on the most pressing research problems.
In addition, don't be fooled into thinking that these attacks only apply to Tor: using Tor is still better than using any other tool, at least in quite a few of these scenarios. That said, some other attacks in the research literature might be even easier than the attacks discussed here. These are fast-moving times for anonymity research. "Maybe you shouldn't use the Internet then" is still the best advice for some people.
Third, the network-level adversaries rely on being able to recognize Tor flows. Does that argue that using pluggable transports, with bridges, might change the equation if it stops the attacker from recognizing Tor users?
Fourth, I should clarify that I don't think any of these large relay-level adversaries actually exist, except as a succession of researchers showing that it can be done. (GCHQ apparently ran a small number of relays a while ago, but not in a volume or duration that would have enabled this attack.) Whereas I *do* think that the network-level attackers exist, since they already invested in being able to surveil the Internet for other reasons. So I think it's great that Aaron's paper presents the dual risks of relay adversaries and link adversaries, since most of the time when people are worrying about one of them they're forgetting the other one.
Fifth, there are still some ways to game the bandwidth authority measurements (here's the spec spec) into giving you more than your fair share of traffic. Ideally we'd adapt a design like EigenSpeed so it can measure fast relays both robustly and accurately. This question also remains a great thesis topic.
And finally, as everybody wants to know: was this attack how "they" busted recent hidden services (Freedom Hosting, Silk Road, the attacks described in the latest Guardian article)? The answer is apparently no in each case, which means the techniques they *did* use were even *lower* hanging fruit. The lesson? Security is hard, and you have to get it right at many different levels.
We've had several requests by the press and others to talk about the Silk Road situation today. We only know what's going on by reading the same news sources everyone else is reading.
In this case we've been watching carefully to try to learn if there are any flaws with Tor that we need to correct. So far, nothing about this case makes us think that there are new ways to compromise Tor (the software or the network). The FBI says that their suspect made mistakes in operational security, and was found through actual detective work. Remember: Tor does not anonymize individuals when they use their legal name on a public forum, use a VPN with logs that are subject to a subpoena, or provide personal information to other services. See also the list of warnings linked from the Tor download page.
Also, while we've seen no evidence that this case involved breaking into the webserver behind the hidden service, we should take this opportunity to emphasize that Tor's hidden service feature (a way to publish and access content anonymously) won't keep someone anonymous when paired with unsafe software or unsafe behavior. It is up to the publisher to choose and configure server software that is resistant to attacks. Mistakes in configuring or maintaining a hidden service website can compromise the publisher's anonymity independent of Tor.
And finally, Tor's design goals include preventing even The Tor Project from tracking users; hidden services are no different. We don't have any special access to or information about this hidden service or any other. Because Tor is open-source and it comes with detailed design documents and research papers, independent researchers can verify its security.
Here are some helpful links to more information on these subjects:
Technical details of hidden services:
Our abuse FAQ:
For those curious about our interactions with law enforcement:
Using Tor hidden services for good:
Regarding the Freedom Hosting incident in August 2013, which is unrelated
as far as we can tell:
Some general hints on staying anonymous:
The Tor Project is a nonprofit 501(c)(3) organization dedicated to providing tools to help people manage their privacy on the Internet. Our focus continues to be in helping ordinary citizens, victims of abuse, individuals in dangerous parts of the world, and others stay aware and educated about how to keep themselves secure online.
The global Tor team remains committed to building technology solutions to help keep the doors to freedom of expression open. We will continue to watch as the details of this situation unfold and respond when it is appropriate and useful.
For further press related questions please contact us at email@example.com.
A Hidden service is a server – often delivering web pages – that is reachable only through the Tor network. While most people know that the Tor network with its thousands of volunteer-run nodes provides anonymity for users who don´t want to be tracked and identified on the internet, the lesser-known hidden service feature of Tor provides anonymity also for the server operator.
Anyone can run hidden services, and many do. We use them internally at The Tor Project to offer our developers anonymous access to services such as SSH, IRC, HTTP, and our bug tracker. Other organizations run hidden services to protect dissidents, activists, and protect the anonymity of users trying to find help for suicide prevention, domestic violence, and abuse-recovery. Whistleblowers and journalists use hidden services to exchange information in a secure and anonymous way and publish critical information in a way that is not easily traced back to them. The New Yorker's Strongbox is one public example.
Hidden service addresses, aka the dot onion domain, are cryptographically and automatically generated by the tor software. They look like this http://idnxcnkne4qt76tg.onion/, which is our torproject.org website as a hidden service.
There is no central repository nor registry of addresses. The dot onion address is both the name and routing address for the services hosted at the dot onion. The Tor network uses the .onion-address to direct requests to the hidden server and route back the data from the hidden server to the anonymous user. The design of the Tor network ensures that the user can not know where the server is located and the server can not find out the IP-address of the user, except by intentional malicious means like hidden tracking code embedded in the web pages delivered by the server. Additionally, the design of the Tor network, which is run by thousands of volunteers, ensures that it is impossible to censor or block certain .onion-addresses.
them if we can.
As for now, one of multiple hidden service hosting companies appears to be down. There are lots of rumors and speculation as to what's happened. We're reading the same news and threads you are and don't have any insider information. We'll keep you updated as details become available.
EDIT: See our next blog post for more details about the attack.
Hidden Services are in a peculiar situation. While they see a loyal fan-base, there are no dedicated Tor developers to take care of them. This results in a big pile of features that need to be researched, implemented and deployed to make Hidden Services more secure and effective.
The purpose of this blog post is threefold:
- Introduce Hidden Service operators to various shortcomings of the Hidden Service architecture.
- Introduce researchers to various research questions regarding Hidden Services.
- Introduce developers to the plethora of coding tasks left to be done in the hidden Service ecosystem.
Note that not every idea listed in the blog post is going to turn out to be a great idea. This post is more of a brain-dump than a solid fully-analyzed agenda.
In any case, let's get down to the issues:
Hidden Service Scaling
The current Hidden Services architecture does not scale well. Ideally, big websites should have the option to completely migrate to Tor Hidden Services, but this is not possible with their current architecture.
One of the main problems with a busy Hidden Service is that its Introduction Points will get hammered by clients. Since Introduction Points are regular Tor relays, they are not intended to handle such load.
Therefore, one of the first steps for improving Hidden Services scalability is increasing the durability of its Introduction Points. Currently, a Hidden Service selects the number of its Introduction Points (between one and ten) based on a self-estimation of its own popularity. Whether the formula currently used is the best such formula is an open research question.
Another problem with Hidden Services is the lack of load balancing options. While you can load-balance a Hidden Service using TCP/HTTP load balancers (like HAProxy), there is no load-balancing option similar to DNS round-robin, where load balancing happens by sending clients to different server IP addresses. Such load-balancing could be achieved by allowing a Hidden Service to have multiple "subservices". Such an architecture, although appealing, introduces multiple problems, like the intercommunication between subservices, where the long-term keypair is stored, how introduction points are assigned, etc.
Defense against Denial of Service of Introduction Points
The adversarial version of the previous section involves attackers intentionally hammering the Introduction Points of a Hidden Service to make it unreachable by honest clients. This means that an attacker can temporarily bring down a Hidden Service by DoSing a small number of Tor relays.
To defend against such attacks, Syverson and Øverlier introduced Valet nodes in their PETS 2006 paper: "Valet Services: Improving Hidden Servers with a Personal Touch". Valet nodes stand in front of Introduction Points and act as a protection layer. This allows Hidden Services to maintain a limited number of Introduction Points, but many more contact points, without clients learning the actual addresses of the Introduction Points.
Valet nodes are not implemented yet, mainly because of the big implementation and deployment effort they require.
The long-term keypair of a Hidden Service is an RSA-1024 keypair which nowadays is considered weak. This means that in the future, Hidden Services will need to migrate to a different keysize and/or asymmetric cryptographic algorithm.
A side effect of such migration is that Hidden Services will get a different onion address, which might be troublesome for Hidden Services that have a well-established onion address. To make the transition smoother, Hidden Services should be able to use both old and new keypairs for a while to be able to point their clients to the new address.
Attacks by Hidden Service Directory Servers
Hidden Services upload their descriptor to Tor nodes called Hidden Service Directory Servers (HSDirs). Clients then fetch that descriptor and use it to connect to the Hidden Service.
In the current system, HSDirs are in an interesting position which allows them to perform the following actions:
- Learn the .onion address of a Hidden Service and connect to it
- Evaluate the popularity of a Hidden Service by tracking the number of clients who do a lookup for that Hidden Service
- Refuse to answer a client, and if enough HSDirs do this then the Hidden Service is temporarily unreachable
These scenarios are explored in the upcoming IEEE S&P paper titled "Trawling for Tor Hidden Services: Detection, Measurement, Deanonymization" from Alex Biryukov, Ivan Pustogarov and Ralf-Philipp Weinmann. Be sure to check it out (once they publish it)!
Let's look at some suggested fixes for the attacks that Hidden Service Directory Servers can perform:
Defences against enumeration of onion addresses
Hidden Services use a hash ring to choose which HSDirs will host their descriptor; this means that HSDirs can just wait to get picked by Hidden Services and then collect their descriptors and onion addresses. Also, since the hash ring is rotating, HSDirs get new Hidden Service descriptors in every rotation period.
One possible solution to this issue would be to append a symmetric key to the onion address and use it to encrypt the descriptor before sending it to HSDirs (similar to how descriptor-cookie authentication works currently). A client that knows the onion address can decrypt the descriptor, but an HSDir who doesn't know the onion address can't derive the Hidden Service name. The drawback of this scheme is that the size of onion addresses will increase without increasing the security of their self-authentication property. Furthermore, HSDirs will still be able to extract the Hidden Service public key from the descriptor, which allows HSDirs to track the descriptors of specific Hidden Services.
A different solution was proposed by Robert Ransom:
Robert's scheme uses the long-term keypair of a Hidden Service to derive (in a one-way fashion) a second keypair, which is used to encrypt and sign the descriptor that is uploaded to the HSDirs. This construction allows the HSDir, without knowing the long-term keypair of the Hidden Service or the contents of its descriptor, to validate that the entity who uploaded the descriptor had possession of the long-term private key of the Hidden Service. A client who knows the long-term public key of the Hidden Service can fetch the descriptor from the HSDir and verify that it was created by the Hidden Service itself. See the relevant trac ticket for a more robust analysis of the idea.
Robert's idea increases the size of onion addresses, but also makes them more resistant to impersonation attacks (the current 80-bit security of onion addresses does not inspire confidence against impresonation attacks). Furthermore, his idea does not allow HSDirs to track Hidden Service descriptors across time.
While Robert's scheme is fairly straightforward, a proper security evaluation is in order and a Tor proposal needs to be written. For extra fun, his idea requires the long-term keypair of the Hidden Service to use a discrete-log cryptosystem, which means that a keypair migration will be needed if we want to proceed with this plan.
Block tracking of popularity of Hidden Services
HSDirs can track the number of users who do a lookup for a Hidden Service, thereby learning how popular they are. We can make it harder for HSDirs to track the popularity of a Hidden Service, by utilizing a Private Information Retrieval (PIR) protocol for Hidden Service descriptor fetches. Of course, this won't stop the Introduction Points of a Hidden Service from doing the tracking, but since the Introduction Points were picked by the Hidden Service itself, the threat is smaller.
If we wanted to block Introduction Points from tracking the popularity of Hidden Services, we could attempt hiding the identity of the Hidden Service from its Introduction Points by using a cookie scheme, similar to how the Rendezvous is currently done, or by using Robert's keypair derivation trick and signing the introduction establishment with the new keypair. A careful security evaluation of these ideas is required.
Make it harder to become an adversarial HSDir
Because of the security implications that HSDirs have for a Hidden Services, we started working on making it harder for a Tor relay to become an HSDir node.
Also, currently, an adversary can predict the identity keys it will need in the future to target a specific Hidden Service. We started thinking of ways to avoid this attack.
Let's investigate some of these proposals:
Reducing Hidden Service Circuit Setup complexity
During PETS 2007 Syverson and Øverlier presented "Improving Efficiency and Simplicity of Tor circuit establishment and hidden services" which simplifies Hidden Service circuit establishmentby eliminating the need of a separate rendezvous connection.
They noticed that by using Valet nodes, the concept of Rendezvous Points is redundant and that a Hidden Service circuit can be formed by just using Valet nodes and Introduction Points. Karsten Loesing wrote a Tor proposal for a variant of this idea.
The reason this scheme is not implemented is that the security trade-offs introduced are not well understood, and there are also some technical obstacles (like the fact that sharing of circuits between multiple clients is not currently supported).
Analyze Hidden Service Circuit Establishment Timing With Torperf
Establishing a connection to a hidden service currently involves two Tor relays, the introduction and rendezvous point, and 10 more relays distributed over four circuits to connect to them. No one has really researched how much time Tor spends in each step of that complicated process. It wouldn't be surprising if a large amount of time is spent in an unexpected part of the process.
To investigate this properly, one should use Torperf to analyze the timing delta between the steps of the process. Unfortunately, Torperf uses controller events to distinguish between Tor protocol phases but not all steps of the Hidden Service circuit setup have controller events assigned to them. Implementing this involves adding the control port triggers to the Tor codebase, running Torperf and then collecting and analyzing the results.
Hidden Services should reuse old Introduction Points
Currently, Hidden Services stop establishing circuits to old Introduction Points after they break. While this behavior makes sense, it means that clients who have old hidden service descriptors will keep introducing themselves to the wrong introduction points. This is especially painful in roaming situations where users frequently change networks (and lose existing circuits).
A solution to this would be for Hidden Services to reestablish failed circuits to old Introduction Points (if the circuits were destroyed because of network failures). We should explore the security consequences of such a move, and also what's the exact time period that Introduction Points are considered "old" but still "worth reestablishing circuits to".
Encrypted Services allow you to run a non-anonymous Hidden Service where the server-side rendezvous circuit is only one hop. This makes sense in scenarios where the Hidden Service doesn't care about its anonymity, but still wants to allow its clients to access it anonymously (and with all the other features that self-authenticating names provide). See Roger's original proposal for more use cases and information.
On this topic, Robert Ransom proposed to implement Encrypted Services as a program separate from Tor, since it serves a quite different threat model. Furthermore, if done this way, its users won't overload the Tor network and it will also allow greater versatility and easier deployment.
Human Memorable onion addresses
Zooko's triangle characterizes onion addresses as secure and global, but not human memorable. By now a couple of schemes have been proposed to make hidden services addresses memorable, but for various reasons none of them has been particularly successful.
These were just some of the things that must be done in the Hidden Services realm. If you are interested in helping around, please read the links and trac tickets, and hit us back with proposals, patches and suggestions. Use the [tor-dev] mailing list, or our IRC channels for development-related communication.
Finally, note that this blog post only touched issues that involve Tor's codebase or the Hidden Service protocol and its cryptography. However, if we want Hidden Services to be truly successful and influential, it's also important to build a vibrant ecosystem around them. For example, we need privacy-preserving archiving systems and search engines (and technologies and rules on how they should work), we need easy-to-use publishing platforms, Internet service daemons and protocols optimized for high-latency connections, anonymous file sharing, chat systems and social networks.
Thanks go to Roger, Robert and other people for the helpful comments and suggestions on this blog post.
PS: Don't forget to use anonbib to find and download any research papers mentioned in this blog post.
Getting good stories for Tor successes is tricky, because if Tor is doing its job, nobody notices. I know a lot of people who have really interesting Tor success stories and have no interest in telling the world who they are and how they managed (until that moment when everybody is reading about them, that is) to stay safe.
Still, there are a bunch of other stories out there that haven't been documented as well. For example, I really like Nasser's story about his experiences in Mauritania:
Hidden services have gotten less broad attention from the Tor user base, since most people who install Tor have a website in mind like twitter or indymedia that they want to visit safely. Some good use cases that we've seen for hidden services in particular include:
- I know people (for example, in countries that have been undergoing revolutions lately) who run popular blogs but their blogs kept getting knocked offline by state-sponsored jerks. The common blogging software they used (like Wordpress) couldn't stand up to the ddos attacks and breakins. The solution was to split the blog into a public side, which is static html and has no logins, and a private side for posting, which is only reachable over a Tor hidden service. Now their blog works again and they're reaching their audiences. And as a bonus, the nice fellow hosting the private side for them doesn't need to let people know where it is, and even if somebody figures it out, the nice fellow hosting it doesn't have any IP addresses to hand over or lose.
- Whistleblowing websites want to provide documents from a platform that is hard for upset corporations or governments to censor. See e.g. http://globaleaks.org/
- Google for 'indymedia fbi seize'. When Indymedia offers a hidden service version of their website, censoring organizations don't know which data centers to bully into handing over the hardware.
- Data retention laws in Europe (and soon in the US too at this rate) threaten to make centralized chat networks vulnerable to social network analysis (step one, collect all the data; step two, get broken into by corporations, criminals, external governments, you name it; step three comes identity theft, stalking, targeted scam jobs, etc etc). What if you had a chat network where all the users were on hidden services by default? Now there's no easy central point to learn who's talking to who and when. Building one and making it usable turns out to be hard. But good thing we have this versatile tool here as a building block.
That's a start. It is certainly the case that we (Tor) spend most of our time making the technology better, and not so much of our time figuring out how to market it and change the world's perception on whether being safe online is worthwhile. Please help. :)
This blog post was adapted from an email to tor-talk by Roger. See the original email at https://lists.torproject.org/pipermail/tor-talk/2011-November/021997.htm...
Tor 0.2.3.9-alpha introduces initial IPv6 support for bridges, adds
a "DisableNetwork" security feature that bundles can use to avoid
touching the network until bridges are configured, moves forward on
the pluggable transport design, fixes a flaw in the hidden service
design that unnecessarily prevented clients with wrong clocks from
reaching hidden services, and fixes a wide variety of other issues.
Changes in version 0.2.3.9-alpha - 2011-12-08
- Clients can now connect to private bridges over IPv6. Bridges
still need at least one IPv4 address in order to connect to
other relays. Note that we don't yet handle the case where the
user has two bridge lines for the same bridge (one IPv4, one
IPv6). Implements parts of proposal 186.
- New "DisableNetwork" config option to prevent Tor from launching any
connections or accepting any connections except on a control port.
Bundles and controllers can set this option before letting Tor talk
to the rest of the network, for example to prevent any connections
to a non-bridge address. Packages like Orbot can also use this
option to instruct Tor to save power when the network is off.
- Clients and bridges can now be configured to use a separate
"transport" proxy. This approach makes the censorship arms race
easier by allowing bridges to use protocol obfuscation plugins. It
implements the "managed proxy" part of proposal 180 (ticket 3472).
- When using OpenSSL 1.0.0 or later, use OpenSSL's counter mode
implementation. It makes AES_CTR about 7% faster than our old one
(which was about 10% faster than the one OpenSSL used to provide).
Resolves ticket 4526.
- Add a "tor2web mode" for clients that want to connect to hidden
services non-anonymously (and possibly more quickly). As a safety
measure to try to keep users from turning this on without knowing
what they are doing, tor2web mode must be explicitly enabled at
compile time, and a copy of Tor compiled to run in tor2web mode
cannot be used as a normal Tor client. Implements feature 2553.
- Add experimental support for running on Windows with IOCP and no
kernel-space socket buffers. This feature is controlled by a new
"UserspaceIOCPBuffers" config option (off by default), which has
no effect unless Tor has been built with support for bufferevents,
is running on Windows, and has enabled IOCP. This may, in the long
run, help solve or mitigate bug 98.
- Use a more secure consensus parameter voting algorithm. Now at
least three directory authorities or a majority of them must
vote on a given parameter before it will be included in the
consensus. Implements proposal 178.
- Hidden services now ignore the timestamps on INTRODUCE2 cells.
They used to check that the timestamp was within 30 minutes
of their system clock, so they could cap the size of their
replay-detection cache, but that approach unnecessarily refused
service to clients with wrong clocks. Bugfix on 0.2.1.6-alpha, when
the v3 intro-point protocol (the first one which sent a timestamp
field in the INTRODUCE2 cell) was introduced; fixes bug 3460.
- Only use the EVP interface when AES acceleration is enabled,
to avoid a 5-7% performance regression. Resolves issue 4525;
bugfix on 0.2.3.8-alpha.
Privacy/anonymity features (bridge detection):
- Make bridge SSL certificates a bit more stealthy by using random
serial numbers, in the same fashion as OpenSSL when generating
self-signed certificates. Implements ticket 4584.
- Introduce a new config option "DynamicDHGroups", enabled by
default, which provides each bridge with a unique prime DH modulus
to be used during SSL handshakes. This option attempts to help
against censors who might use the Apache DH modulus as a static
identifier for bridges. Addresses ticket 4548.
Minor features (new/different config options):
- New configuration option "DisableDebuggerAttachment" (on by default)
to prevent basic debugging attachment attempts by other processes.
Supports Mac OS X and Gnu/Linux. Resolves ticket 3313.
- Allow MapAddress directives to specify matches against super-domains,
as in "MapAddress *.torproject.org *.torproject.org.torserver.exit".
Implements issue 933.
- Slightly change behavior of "list" options (that is, config
options that can appear more than once) when they appear both in
torrc and on the command line. Previously, the command-line options
would be appended to the ones from torrc. Now, the command-line
options override the torrc options entirely. This new behavior
allows the user to override list options (like exit policies and
ports to listen on) from the command line, rather than simply
appending to the list.
- You can get the old (appending) command-line behavior for "list"
options by prefixing the option name with a "+".
- You can remove all the values for a "list" option from the command
line without adding any new ones by prefixing the option name
with a "/".
- Add experimental support for a "defaults" torrc file to be parsed
before the regular torrc. Torrc options override the defaults file's
options in the same way that the command line overrides the torrc.
The SAVECONF controller command saves only those options which
differ between the current configuration and the defaults file. HUP
reloads both files. (Note: This is an experimental feature; its
behavior will probably be refined in future 0.2.3.x-alpha versions
to better meet packagers' needs.)
- Try to make the introductory warning message that Tor prints on
startup more useful for actually finding help and information.
Resolves ticket 2474.
- Running "make version" now displays the version of Tor that
we're about to build. Idea from katmagic; resolves issue 4400.
- Expire old or over-used hidden service introduction points.
Required by fix for bug 3460.
- Move the replay-detection cache for the RSA-encrypted parts of
INTRODUCE2 cells to the introduction point data structures.
Previously, we would use one replay-detection cache per hidden
service. Required by fix for bug 3460.
- Reduce the lifetime of elements of hidden services' Diffie-Hellman
public key replay-detection cache from 60 minutes to 5 minutes. This
replay-detection cache is now used only to detect multiple
INTRODUCE2 cells specifying the same rendezvous point, so we can
avoid launching multiple simultaneous attempts to connect to it.
Minor bugfixes (on Tor 0.2.2.x and earlier):
- Resolve an integer overflow bug in smartlist_ensure_capacity().
Fixes bug 4230; bugfix on Tor 0.1.0.1-rc. Based on a patch by
- Fix a minor formatting issue in one of tor-gencert's error messages.
Fixes bug 4574.
- Prevent a false positive from the check-spaces script, by disabling
the "whitespace between function name and (" check for functions
- Fix a log message suggesting that people contact a non-existent
email address. Fixes bug 3448.
- Fix null-pointer access that could occur if TLS allocation failed.
Fixes bug 4531; bugfix on 0.2.0.20-rc. Found by "troll_un".
- Report a real bootstrap problem to the controller on router
identity mismatch. Previously we just said "foo", which probably
made a lot of sense at the time. Fixes bug 4169; bugfix on
- If we had ever tried to call tor_addr_to_str() on an address of
unknown type, we would have done a strdup() on an uninitialized
buffer. Now we won't. Fixes bug 4529; bugfix on 0.2.1.3-alpha.
Reported by "troll_un".
- Correctly detect and handle transient lookup failures from
tor_addr_lookup(). Fixes bug 4530; bugfix on 0.2.1.5-alpha.
Reported by "troll_un".
- Use tor_socket_t type for listener argument to accept(). Fixes bug
4535; bugfix on 0.2.2.28-beta. Found by "troll_un".
- Initialize conn->addr to a valid state in spawn_cpuworker(). Fixes
bug 4532; found by "troll_un".
Minor bugfixes (on Tor 0.2.3.x):
- Fix a compile warning in tor_inet_pton(). Bugfix on 0.2.3.8-alpha;
fixes bug 4554.
- Don't send two ESTABLISH_RENDEZVOUS cells when opening a new
circuit for use as a hidden service client's rendezvous point.
Fixes bugs 4641 and 4171; bugfix on 0.2.3.3-alpha. Diagnosed
with help from wanoskarnet.
- Restore behavior of overriding SocksPort, ORPort, and similar
options from the command line. Bugfix on 0.2.3.3-alpha.
- Properly handle the case where the build-tree is not the same
as the source tree when generating src/common/common_sha1.i,
src/or/micro-revision.i, and src/or/or_sha1.i. Fixes bug 3953;
bugfix on 0.2.0.1-alpha.
Code simplifications, cleanups, and refactorings:
- Remove the pure attribute from all functions that used it
previously. In many cases we assigned it incorrectly, because the
functions might assert or call impure functions, and we don't have
evidence that keeping the pure attribute is worthwhile. Implements
changes suggested in ticket 4421.
- Remove some dead code spotted by coverity. Fixes cid 432.
Bugfix on 0.2.3.1-alpha, closes bug 4637.
There are two recent stories claiming the Tor network is compromised. It seems it is easier to get press than to publish research, work with us on the details, and propose solutions. Our comments here are based upon the same stories you are reading. We have no insider information.
The first story has been around 'Freedom Hosting' and their hosting of child abuse materials as exposed by Anonymous Operation Darknet. We're reading the press articles, pastebin urls, and talking to the same people as you. It appears 'Anonymous' cracked the Apache/PHP/MySQL setup at Freedom Hosting and published some, or all, of their users in the database. These sites happened to be hosted on a Tor hidden service. Further, 'Anonymous' used a somewhat recent RAM-exhaustion denial of service attack on the 'Freedom Hosting' Apache server. It's a simple resource starvation attack that can be conducted over low bandwidth, low resource requirement connections to individual hosts. This isn't an attack on Tor, but rather an attack on some software behind a Tor hidden service. This attack was discussed in a thread on the tor-talk mailing list starting October 19th.
The second story is around Eric Filiol's claims of compromising the Tor network leading up to his Hackers to Hackers talk in Brazil in a few days. This claim was initially announced by some French websites; however, it has spread further, such as this Hacker News story.
Again, the tor-talk mailing list had the first discussions of these attacks back on October 13th. To be clear, neither Eric nor his researchers have disclosed anything about this attack to us. They have not talked to us, nor shared any data with us — despite some mail exchanges where we reminded him about the phrase "responsible disclosure".
Here's the attack as we understand it, from reading the various press reports:
They enumerated 6000 IP addresses that they think are Tor relays. There aren't that many Tor relays in the world — 2500 is a more accurate number. We're not sure what caused them to overcount so much. Perhaps they watched the Tor network over a matter of weeks and collected a bunch of addresses that aren't relays anymore? The set of relays is public information, so there's no reason to collect your own list and certainly no reason to end up with a wrong list.
One-third of the machines on those IP addresses are vulnerable to operating system or other system level attacks, meaning he can break in. That's quite a few! We wonder if that's true with the real Tor network, or just their simulated one? Even ignoring the question of what these 3500 extra IP addresses are, it's important to remember that one-third by number is not at all the same as one-third by capacity: Tor clients load-balance over relays based on the relay capacity, so any useful statement should be about how much of the capacity of the Tor network is vulnerable. It would indeed be shocking if one-third of the Tor network by capacity is vulnerable to external attacks.
(There's also an aside about enumerating bridges. They say they found 181 bridges, and then there's a quote saying they "now have a complete picture of the topography of Tor", which is a particularly unfortunate time for that quote since there are currently around 600 bridges running.)
We expect the talk will include discussion about some cool Windows trick that can modify the crypto keys in a running Tor relay that you have local system access to; but it's simpler and smarter just to say that when the attacker has local system access to a Tor relay, the attacker controls the relay.
Once they've broken into some relays, they do congestion attacks like packet spinning to congest the relays they couldn't compromise, to drive users toward the relays they own. It's unclear how many resources are needed to keep the rest of the relays continuously occupied long enough to keep the user from using them. There are probably some better heuristics that clients can use to distinguish between a loaded relay and an unavailable relay; we look forward to learning how well their attack here actually worked.
From there, the attack gets vague. The only hint we have is this nonsense sentence from the article:
The remaining flow can then be decrypted via a fully method of attack called "to clear unknown" based on statistical analysis.
Do they have a new attack on AES, or on OpenSSL's implementation of it, or on our use of OpenSSL? Or are they instead doing some sort of timing attack, where if you own the client's first hop and also the destination you can use statistics to confirm that the two flows are on the same circuit? There's a history of confused researchers proclaiming some sort of novel active attack when passive correlation attacks are much simpler and just as effective.
So the summary of the attack might be "take control of the nodes you can, then congest the other ones so your targets avoid them and use the nodes you control. Then do some unspecified magic crypto attack to defeat the layers of encryption for later hops in the circuit." But really, these are just guesses based on the same news articles you're reading. We look forwarding to finding out if there's actually an attack we can fix, or if they are just playing all the journalists to get attention.
More generally, there are two broader lessons to remember here. First, research into anonymity-breaking attacks is how the field moves forward, and using Tor for your target is common because a) it's resistant to all the simpler attacks and b) we make it really easy to do your research on. And second, remember that most other anonymity systems out there fall to these attacks so quickly and thoroughly that no researchers even talk about it anymore. For some recent examples, see the single-hop proxy discussions in How Much Anonymity does Network Latency Leak? and Website Fingerprinting in Onion Routing Based Anonymization Networks.
I thank Roger, Nick, and Runa for helping with this post.