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Re: [tor-dev] Proposal xxx: Filtering malicious rendezvous points at hidden service server side



On 23 Jan (23:38:00), s7r wrote:
> Hello,
> 
> Inspired by asn, dgoulet and Mike Perry discussing alternate path
> lengths for proposal 247, I wrote a proposal that could fit in nicely
> with proposal 247, maybe even allow us to make the 3rd hop wild
> (random) so we don't have to worry about HSDirs + HSDir fetch/post
> circuits and introduction points + introduction points circuits
> linking short term layer 3 guards.
> 
> Please find the proposal attached as well as inline for comments.
> Looking forward for reviews.
> 
> If I've structured it wrong or something I apologize in advance - will
> do better next time.
> 
> 
> 
> Filename: xxx-malicious-rendezvous-point-filter.txt
> Title: Filtering malicious rendezvous points at hidden service server side
> Authors: s7r [ 0x837FA52C81265B11 ]
> Created: 23 January 2016
> Status: Draft
> 
> 0. Definitions
> 
> client = an user running Tor as a client, which connects to a hidden
> service.
> hidden service server = the Tor instance hosting the hidden service.
> rendezvous point = the relay which acts as the rendezvous meeting
> point in a circuit between a hidden service client and a hidden
> service server.
> 
> 
> 1. Motivation
> 
> A hidden service circuit (rendezvous circuit) is always initiated by
> the client so the relay which should act as the rendezvous meeting
> point is selected by the client. We assume that any client can be an
> attacker and will try to make the hidden service server connect to a
> malicious rendezvous point under his control.
> 	
> The attacker is also a Sybil (holds an unknown % of the bandwidth in
> the Tor network). By making the hidden service server build many
> circuits to his evil rendezvous points, the attacker gets a high
> probability that the hidden service server will eventually pick his
> evil relays in a circuit, so the attacker will trivially perform a
> successful hidden service guard discovery attack or, with more luck,
> discover the real location of the hidden service server.
> 	
> The hidden service server can only defend itself by building a 3 hop
> circuit to the rendezvous point, but in practice this is not always
> enough.
> 
> 
> 2. Logic for filtering malicious rendezvous points
> 
> To be able to make fair assumptions about which rendezvous point might
> be malicious or not we are going to use the probability theory and
> statistics, precisely the binominal distribution equation [0].
> 	
> In simple words, we count and keep track of how many rendezvous
> circuits a hidden service server built and to which rendezvous points.
> Then, based on the weight (middle probability fraction) of each
> rendezvous point, we determine if one was insanely overpicked by
> clients. Think of this like: Alice plays a game with Bob in which Bob
> has the success probability to draw a certain number n%. In practice
> however, he shows a success rate of more than (n*2)% (2 times bigger),
> Alice assumes Bob is not playing nice and will refuse to play with him
> for the next 24 hours or so.
> 	
> Fast example:
> A hidden service server built 100 rendezvous circuits in the last 24
> hours, out of which in 7 of them the rendezvous point was a relay with
> the middle probability fraction of 0.5%. We assume that rendezvous
> point is malicious and refuse to build rendezvous circuits to it for
> the next 24 hours.

Can you explain to me why 24 hours here? Why not 12 hours or one hour?
I'm fine if it's some values that popped in your mind but if it's not,
explaining why would be helpful.

> 	
> 	
> 3. Equations and formulas
> 
> 3.1 Probability of different clients genuinely picking the same
> rendezvous point
> n = total number of established rendezvous circuits.
> k = number of clients that could have genuinely picked the same
> rendezvous point.
> p = probability of picking that rendezvous point per client (middle
> probability fraction of the relay) divided to 100.
> H = Probability mass function expanded.
> C = The result of the equation, the value we need to determine
> multiplied with 100 to have the percent value.
> 	
> Formulas:
> H = n! / k!^(n - k)!
> C = H * p^k * (1 - p)^n - k
> 	
> Example:
> n = 100
> k = 9
> p = 0.5% / 100 = 0.005
> 	
> H = 100! / 9!^91! = 20023492720
> C = 20023492720 * 0.000000000000000000001953125 * 0.63372, ~
> 0.00000000002478376524710625 * 100, ~ 0.000000002478376524710625%
> 	
> 3.2 Expected number of clients to pick the same rendezvous point
> n = Total number of established rendezvous circuits.
> p = Probability of picking that rendezvous point per client (middle
> probability fraction of the relay) divided to 100. We multiply this
> with 2 intentionally so we will allow 2 times more circuits than we
> would expect based on this formula - this should reduce the error
> margin enough.
> C = The result of the equation, the value we need to determine.
> 	
> Formula:
> C = n * p
> 	
> Example:
> n = 100
> p = 0.5% / 100 = 0.005 * 2 = 0.01
> 
> C = 100 * 0.01 = 1
> 	
> 	
> 4. Implementation and variables
> 
> We keep track in the persistent state of a hidden service server of
> the total number of built rendezvous circuits as well as a counter for
> number of rendezvous circuits per rendezvous point.
> 	
> Variables:
> REND_FILTER_MONITOR_PERIOD = count and track the rendezvous circuits
> built within this latest period. We set it to 24 hours.
> 
> REND_FILTER_BAN_PERIOD = for how long we are going to ban a malicious
> rendezvous point. We set it to 24 hours.
> 	
> REND_FILTER_TOLERANCE = how many circuits we allow per rendezvous
> point regardless of its middle probability fraction. We set it to 4.
> 	
> REND_FILTER_BAN_ACTIVATION = when we should ban a malicious rendezvous
> point. To determine this, we are going to get from
> REND_FILTER_MONITOR_PERIOD the total number of established rendezvous
> circuits as well as the number of established rendezvous circuits with
> a given rendezvous point and apply the formula from 3.2 with
> approximation to the next whole number (example: 5.01 = 6; 5.99 = 6).
> 	
> Example: A hidden service server built 100 circuits in the last 24
> hours out of which 5 to a rendezvous point with the middle probability
> fraction 1% (p = 0.02), so the expected number of circuits we expect
> is 2, but allow up to maximum 4 (if REND_FILTER_TOLERANCE >
> REND_FILTER_BAN_ACTIVATION, REND_FILTER_TOLERANCE prevails). In this
> case we consider this too much of a coincidence and ban this
> rendezvous point for the next 24 hours. We keep this ban in our
> persistent state with a timestamp so we'll know when it expires.
> 	

What I would like to see in this proposal, and this might ties to what
Mike asked, is a table that shows the effort needed for an attacker that
tries to blacklist all nodes. How much circuit per RP will be needed as
the attack evolve. 10 RP == how many circuits, then 100 then 1000. If I
had 200 clients opening circuits, how much time and circuits will I need
too blacklist all RP?

Your explanation on another email about this explains how the more
circuits the more difficult it gets to black list node but still I'm not
convinced that it's that difficult. The overloaded Guard argument can
make sense here but 24h is along time so an attacker can try multiple
patterns of circuits that might not overload the hs guard.

> 	
> 5. Ban malicious rendezvous points just for rendezvous circuits, not
> for anything else
> 
> If we treat as relay as a malicious rendezvous point for a given time
> period, this only means we are not building circuits with it as the
> rendezvous point, but we don't exclude it for other purpose circuits,
> regardless which are those other purpose circuits. We may use them in
> our exit circuits, consensus fetch circuits, as HSDirs and HSDir fetch
> / post circuits, as Introduction Points or Introduction Point circuits.
> 	
> 
> 6. Non zero probability to assign the malicious rendezvous point flag
> to an innocent relay
> 
> This is indeed a non-zero value and it can be computed with the
> formula from 3.1, but it's a value so close to zero that we think it's
> totally worth it.
> 	
> Even if accidentally (low chances) an innocent relay will be banned,
> this will be something local to the hidden service server. It won't
> affect that relay at all, nor how other client or hidden service
> servers treat that relay. It has nothing to do with the network wide
> consensus as well.
> 	
> A honest client will always retry with a different rendezvous point,
> so honest clients should not experience reachability issues.

I confirm that Roger is right. See
circuit_get_ready_rend_circ_by_rend_data() and how it's used, client
will reuse a rend circuit as long as it's alive.

That can complicates thing a bit here because if by any chance that RP
gets blacklisted then the client will retry some more times and
ultimately failing to connect. Implementing this defense will probably
also required some client tweaks...

Thanks!
David

> 	
> 
> 7. Rendezvous points that aren't included in hidden service server's
> consensus
> 
> Clients and hidden service servers might have different consensuses.
> This means that a hidden service server can be genuinely asked to
> build a rendezvous circuit to a rendezvous point for which it has no
> middle probability fraction because it's not included in that
> consensus. We should allow REND_FILTER_TOLERANCE number of circuits to
> the rendezvous points for which we have no weights at all and if that
> rendezvous point appears in a later consensus within the
> REND_FILTER_MONITOR_PERIOD update its middle probability fraction
> value to ensure the filter will activate and work properly once
> REND_FILTER_TOLERANCE threshold was reached.
> 	
> 	
> 8. Security implications for maintaining such records in the
> persistent state of a hidden service server
> 
> An attacker which compromises the location of a hidden service server
> will access this additional information: total number of rendezvous
> circuits built within the last REND_FILTER_MONITOR_PERIOD and to which
> rendezvous points these circuits were. This tradeoff should be worth
> it as well, since if the location of a hidden service server is
> compromised it is game over anyway, and this additional information
> shouldn't be so important to the attacker, except maybe for better
> determining the popularity of that hidden service (this can be
> determined many other ways, like the logs from the application running
> behind the hidden service, network counter, datacenter/ISP level
> counters and logs, etc.).
> 
> To avoid co-location linkability between different hidden services, we
> should keep rendezvous circuits records and counters individually for
> each hidden service.
> 	
> The logic is designed to adjust by itself dynamically, based on the
> popularity and usage of a hidden service. If it's a high profile
> hidden service, experiencing 10000 connections per 24 hours, the
> REND_FILTER_BAN_ACTIVATION will increase for every rendezvous point.
> 	
> 	
> 9. Default option, with possibility to turn off for testing
> environments and experiments
> 
> We add a new torrc option named HiddenServiceRendFilter 0|1 and set it
> to 1 by default. It can be turned off by setting it to 0, if this will
> be desired in some testing environments or experiments.
> 	
> 
> 10. Other considerations, limitations and compatibility with other
> existing proposals
> 	
> This proposal won't disable an attacker entirely, but it will make it
> much harder and more expensive, given that the attacker will have to
> run more malicious relays to act as rendezvous points, increasing the
> capacity of the Tor network overall and directly the costs of the
> attack. Also, the attacker will have to grow the popularity of a
> hidden service so that he can establish more rendezvous circuits using
> the same rendezvous points. This will at least be kind of hard if
> other genuine clients pick the same rendezvous points and get noisy to
> the hidden service operator (much more traffic, same number or
> slightly more users on his service).
> 	
> This proposal is compatible with all the other hidden service related
> proposals to date. For tools like OnionBalance, each backend /
> fallback Tor instance included in the master hidden service descriptor
> will just transparently and individually maintain their own tracking
> vales and ban list.
> 	
> With proposal 260 - Rendezvous Single Onion Services this should be
> disabled since it makes no sense. Set HiddenServiceRendFilter 0 in a
> RSOS type hidden service.
> 	
> This proposal should be quite helpful once we implement enough padding
> between relays, where an attacker might have to own the entire path in
> order to distinguish dummy traffic from real traffic.
> 	
> This proposal should fit in nicely with proposal 247 - Vanguards and
> could make it safe to leave the 3rd hop wild (no layer 3 short term
> guards) and use only layer 2 medium term guards + layer 1 long term
> guard since an attacker will be able to establish less circuits to his
> malicious rendezvous point, thus drastically decreasing the chances of
> the hidden service server to also pick his malicious relay as 3rd hop
> to the malicious rendezvous point (layer 2 guards discovery).
> 
> 
> [0]: https://en.wikipedia.org/wiki/Binomial_distribution

> Filename: xxx-malicious-rendezvous-point-filter.txt
> Title: Filtering malicious rendezvous points at hidden service server side
> Authors: s7r [ 0x837FA52C81265B11 ]
> Created: 23 January 2016
> Status: Draft
> 
> 0. Definitions
> 
> 	client = an user running Tor as a client, which connects to a hidden service.
> 	hidden service server = the Tor instance hosting the hidden service.
> 	rendezvous point = the relay which acts as the rendezvous meeting point in a circuit between a hidden service client and a hidden service server.
> 
> 
> 1. Motivation
> 
> 	A hidden service circuit (rendezvous circuit) is always initiated by the client so the relay which should act as the rendezvous meeting point is selected by the client. We assume that any client can be an attacker and will try to make the hidden service server connect to a malicious rendezvous point under his control. 
> 	
> 	The attacker is also a Sybil (holds an unknown % of the bandwidth in the Tor network). By making the hidden service server build many circuits to his evil rendezvous points, the attacker gets a high probability that the hidden service server will eventually pick his evil relays in a circuit, so the attacker will trivially perform a successful hidden service guard discovery attack or, with more luck, discover the real location of the hidden service server.
> 	
> 	The hidden service server can only defend itself by building a 3 hop circuit to the rendezvous point, but in practice this is not always enough.
> 
> 
> 2. Logic for filtering malicious rendezvous points
> 
> 	To be able to make fair assumptions about which rendezvous point might be malicious or not we are going to use the probability theory and statistics, precisely the binominal distribution equation [0].
> 	
> 	In simple words, we count and keep track of how many rendezvous circuits a hidden service server built and to which rendezvous points. Then, based on the weight (middle probability fraction) of each rendezvous point, we determine if one was insanely overpicked by clients. Think of this like: Alice plays a game with Bob in which Bob has the success probability to draw a certain number n%. In practice however, he shows a success rate of (n*2)% (2 times bigger), Alice assumes Bob is not playing nice and will refuse to play with him for the next 24 hours or so.
> 	
> 	Fast example: 
> 	A hidden service server built 100 rendezvous circuits in the last 24 hours, out of which in 5 of them the rendezvous point was a relay with the middle probability fraction of 0.5%. We assume that rendezvous point is malicious and refuse to build rendezvous circuits to it for the next 24 hours.
> 	
> 	
> 3. Equations and formulas
> 
> 3.1 Probability of different clients genuinely picking the same rendezvous point
> 	n = total number of established rendezvous circuits.
> 	k = number of clients that could have genuinely picked the same rendezvous point.
> 	p = probability of picking that rendezvous point per client (middle probability fraction of the relay) divided to 100.
> 	H = Probability mass function expanded.
> 	C = The result of the equation, the value we need to determine multiplied with 100 to have the percent value.
> 	
> 	Formulas:
> 	H = n! / k!^(n - k)!
> 	C = H * p^k * (1 - p)^n - k
> 	
> 	Example:
> 	n = 100
> 	k = 9
> 	p = 0.5% / 100 = 0.005
> 	
> 	H = 100! / 9!^91! = 20023492720
> 	C = 20023492720 * 0.000000000000000000001953125 * 0.63372, ~ 0.00000000002478376524710625 * 100, ~ 0.000000002478376524710625%
> 	
> 3.2 Expected number of clients to pick the same rendezvous point
> 	n = Total number of established rendezvous circuits.
> 	p = Probability of picking that rendezvous point per client (middle probability fraction of the relay) divided to 100. We multiply this with 2 intentionally so we will allow 2 times more circuits than we would expect based on this formula - this should reduce the error margin enough.
> 	C = The result of the equation, the value we need to determine.
> 	
> 	Formula:
> 	C = n * p
> 	
> 	Example:
> 	n = 100
> 	p = 0.5% / 100 = 0.005 * 2 = 0.01
> 	
> 	C = 100 * 0.01 = 1
> 	
> 	
> 4. Implementation and variables
> 
> 	We keep track in the persistent state of a hidden service server of the total number of built rendezvous circuits as well as a counter for number of rendezvous circuits per rendezvous point.
> 	
> 	Variables:
> 	REND_FILTER_MONITOR_PERIOD = count and track the rendezvous circuits built within this latest period. We set it to 24 hours.
> 
> 	REND_FILTER_BAN_PERIOD = for how long we are going to ban a malicious rendezvous point. We set it to 24 hours.
> 	
> 	REND_FILTER_TOLERANCE = how many circuits we allow per rendezvous point regardless of its middle probability fraction. We set it to 4.
> 	
> 	REND_FILTER_BAN_ACTIVATION = when we should ban a malicious rendezvous point. To determine this, we are going to get from REND_FILTER_MONITOR_PERIOD the total number of established rendezvous circuits as well as the number of established rendezvous circuits with a given rendezvous point and apply the formula from 3.2 with approximation to the next whole number (example: 5.01 = 6; 5.99 = 6).
> 	
> 	Example: A hidden service server built 100 circuits in the last 24 hours out of which 5 to a rendezvous point with the middle probability fraction 1% (p = 0.01), so the expected number of circuits we expect is 2, but allow up to maximum 4 (if REND_FILTER_TOLERANCE > REND_FILTER_BAN_ACTIVATION, REND_FILTER_TOLERANCE prevails). In this case we consider this too much of a coincidence and ban this rendezvous point for the next 24 hours. We keep this ban in our persistent state with a timestamp so we'll know when it expires.
> 	
> 	
> 5. Ban malicious rendezvous points just for rendezvous circuits, not for anything else
> 
> 	If we treat as relay as a malicious rendezvous point for a given time period, this only means we are not building circuits with it as the rendezvous point, but we don't exclude it for other purpose circuits, regardless which are those other purpose circuits. We may use them in our exit circuits, consensus fetch circuits, as HSDirs and HSDir fetch / post circuits, as Introduction Points or Introduction Point circuits.
> 	
> 
> 6. Non zero probability to assign the malicious rendezvous point flag to an innocent relay
> 
> 	This is indeed a non-zero value and it can be computed with the formula from 3.1, but it's a value so close to zero that we think it's totally worth it.
> 	
> 	Even if accidentally (low chances) an innocent relay will be banned, this will be something local to the hidden service server. It won't affect that relay at all, nor how other client or hidden service servers treat that relay. It has nothing to do with the network wide consensus as well.
> 	
> 	A honest client will always retry with a different rendezvous point, so honest clients should not experience reachability issues.
> 	
> 
> 7. Rendezvous points that aren't included in hidden service server's consensus
> 
> 	Clients and hidden service servers might have different consensuses. This means that a hidden service server can be genuinely asked to build a rendezvous circuit to a rendezvous point for which it has no middle probability fraction because it's not included in that consensus. We should allow REND_FILTER_TOLERANCE number of circuits to the rendezvous points for which we have no weights at all and if that rendezvous point appears in a later consensus within the REND_FILTER_MONITOR_PERIOD update its middle probability fraction value to ensure the filter will activate and work properly once REND_FILTER_TOLERANCE threshold was reached.
> 	
> 	
> 8. Security implications for maintaining such records in the persistent state of a hidden service server
> 
> 	An attacker which compromises the location of a hidden service server will access this additional information: total number of rendezvous circuits built within the last REND_FILTER_MONITOR_PERIOD and to which rendezvous points these circuits were. This tradeoff should be worth it as well, since if the location of a hidden service server is compromised it is game over anyway, and this additional information shouldn't be so important to the attacker, except maybe for better determining the popularity of that hidden service (this can be determined many other ways, like the logs from the application running behind the hidden service, network counter, datacenter/ISP level counters and logs, etc.).
> 
> 	To avoid co-location linkability between different hidden services, we should keep rendezvous circuits records and counters individually for each hidden service. 
> 	
> 	The logic is designed to adjust by itself dynamically, based on the popularity and usage of a hidden service. If it's a high profile hidden service, experiencing 10000 connections per 24 hours, the REND_FILTER_BAN_ACTIVATION will increase for every rendezvous point.
> 	
> 	
> 9. Default option, with possibility to turn off for testing environments and experiments
> 
> 	We add a new torrc option named HiddenServiceRendFilter 0|1 and set it to 1 by default. It can be turned off by setting it to 0, if this will be desired in some testing environments or experiments.
> 	
> 
> 10. Other considerations, limitations and compatibility with other existing proposals
> 	
> 	This proposal won't disable an attacker entirely, but it will make it much harder and more expensive, given that the attacker will have to run more malicious relays to act as rendezvous points, increasing the capacity of the Tor network overall and directly the costs of the attack. Also, the attacker will have to grow the popularity of a hidden service so that he can establish more rendezvous circuits using the same rendezvous points. This will at least be kind of hard if other genuine clients pick the same rendezvous points and get noisy to the hidden service operator (much more traffic, same number or slightly more users on his service).
> 	
> 	This proposal is compatible with all the other hidden service related proposals to date. For tools like OnionBalance, each backend / fallback Tor instance included in the master hidden service descriptor will just transparently and individually maintain their own tracking valuse and ban list. 
> 	
> 	With proposal 260 - Rendezvous Single Onion Services this should be disabled since it makes no sense. Set HiddenServiceRendFilter 0 in a RSOS type hidden service.
> 	
> 	This proposal should be quite helpful once we implement enough padding between relays, where an attacker might have to own the entire path in order to distinguish dummy traffic from real traffic.
> 	
> 	This proposal should fit in nicely with proposal 247 - Vanguards and could make it safe to leave the 3rd hop wild (no layer 3 short term guards) and use only layer 2 medium term guards + layer 1 long term guard since an attacker will be able to establish less circuits to his malicious rendezvous point, thus drastically decreasing the chances of the hidden service server to also pick his malicious relay as 3rd hop to the malicious rendezvous point (layer 2 guards discovery).
> 	
> [0]: https://en.wikipedia.org/wiki/Binomial_distribution

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