[tor-dev] [RFC] Proposal: A First Take at PoW Over Introduction Circuits
George Kadianakis
desnacked at riseup.net
Thu Apr 2 15:54:59 UTC 2020
Hello list,
hope everyone is safe and doing well!
I present you an initial draft of a proposal on PoW-based defences for
onion services under DoS.
The proposal is not finished yet and it needs tuning and fixing. There
are many places marked with XXX and TODO around the proposal that should
be addressed.
The important part is that looking at the numbers it does seem like this
proposal can work as a concept and serve its intended purpose. The most
handwavey parts of the proposal right now are [INTRO_QUEUE] and
[POW_SECURITY] and if this thing fails in the end, it's probably gonna
be something that slipped over there. Hence, we should polish these
sections before we proceed with any sort of engineering here.
In any case, I decided to send it to the list even in premature form, so
that it can serve as a stable point of reference in subsequent
discussions. It can also be found in my git repo:
https://github.com/asn-d6/torspec/tree/pow-over-intro
Cheers and stay safe!
---
Filename: xxx-pow-over-intro-v1
Title: A First Take at PoW Over Introduction Circuits
Author: George Kadianakis
Created: 2 April 2020
Status: Draft
0. Abstract
This proposal aims to thwart introduction flooding DoS attacks by introducing
a dynamic Proof-Of-Work protocol that occurs over introduction circuits.
1. Motivation
So far our attempts at limiting the impact of introduction flooding DoS
attacks on onion services has been focused on horizontal scaling with
Onionbalance, optimizing the CPU usage of Tor and applying congestion control
using rate limiting. While these measures move the goalpost forward, a core
problem with onion service DoS is that building rendezvous circuits is a
costly procedure both for the service and for the network. If we ever hope to
have truly reachable global onion services, we need to make it harder for
attackers to overload the service with introduction requests.
This proposal achieves this by allowing onion services to specify an optional
dynamic proof-of-work scheme that its clients need to participate in if they
want to get served.
With the right parameters, this proof-of-work scheme acts as a gatekeeper to
block amplification attacks by attackers while letting legitimate clients
through.
1.1. Threat model [THREAT_MODEL]
1.1.1. Attacker profiles [ATTACKER_MODEL]
This proposal is written to thwart specific attackers. A simple PoW proposal
cannot defend against all and every DoS attack on the Internet, but there are
adverary models we can defend against.
Let's start with some adversary profiles:
"The script-kiddie"
The script-kiddie has a single computer and pushes it to its
limits. Perhaps it also has a VPS and a pwned server. We are talking about
an attacker with total access to 10 Ghz of CPU and 10 GBs of RAM. We
consider the total cost for this attacker to be zero $.
"The small botnet"
The small botnet is a bunch of computers lined up to do an introduction
flooding attack. Assuming 500 medium-range computers, we are talking about
an attacker with total access to 10 Thz of CPU and 10 TB of RAM. We consider
the upfront cost for this attacker to be about $400.
"The large botnet"
The large botnet is a serious operation with many thousands of computers
organized to do this attack. Assuming 100k medium-range computers, we are
talking about an attacker with total access to 200 Thz of CPU and 200 TB of
RAM. The upfront cost for this attacker is about $36k.
We hope that this proposal can help us defend against the script-kiddie
attacker and small botnets. To defend against a large botnet we would need
more tools in our disposal (see [FUTURE_WORK]).
{XXX: Do the above make sense? What other attackers do we care about? What
other metrics do we care about? Network speed? I got the botnet costs
from here [REF_BOTNET] Back up our claims of defence.}
1.1.2. User profiles [USER_MODEL]
We have attackers and we have users. Here are a few user profiles:
"The standard web user"
This is a standard laptop/desktop user who is trying to browse the
web. They don't know how these defences work and they don't care to
configure or tweak them. They are gonna use the default values and if the
site doesn't load, they are gonna close their browser and be sad at Tor.
They run a 2Ghz computer with 4GB of RAM.
"The motivated user"
This is a user that really wants to reach their destination. They don't
care about the journey; they just want to get there. They know what's going
on; they are willing to tweak the default values and make their computer do
expensive multi-minute PoW computations to get where they want to be.
"The mobile user"
This is a motivated user on a mobile phone. Even tho they want to read the
news article, they don't have much leeway on stressing their machine to do
more computation.
We hope that this proposal will allow the motivated user to always connect
where they want to connect to, and also give more chances to the other user
groups to reach the destination.
1.1.3. The DoS Catch-22 [CATCH22]
This proposal is not perfect and it does not cover all the use cases. Still,
we think that by covering some use cases and giving reachability to the
people who really need it, we will severely demotivate the attackers from
continuing the DoS attacks and hence stop the DoS threat all
together. Furthermore, by increasing the cost to launch a DoS attack, a big
class of DoS attackers will disappear from the map, since the expected ROI
will decrease.
2. System Overview
2.1. Tor protocol overview
+----------------------------------+
| |
+-------+ INTRO1 +-----------+ INTRO2 +--------+ |
|Client |-------->|Intro Point|------->| PoW |-----------+ |
+-------+ +-----------+ |Verifier| | |
+--------+ | |
| | |
| | |
| +----------v---------+ |
| |Intro Priority Queue| |
+---------+--------------------+---+
| | |
Rendezvous | | |
circuits | | |
v v v
The proof-of-work scheme specified in this proposal takes place during the
introduction phase of the onion service protocol. It's an optional mechanism
that only occurs if the service requires it. It can be enabled and disabled
either through its torrc or through the control port.
In summary, the following steps are taken for the protocol to complete:
1) Service encodes PoW parameters in descriptor [DESC_POW]
2) Client fetches descriptor and computes PoW [CLIENT_POW]
3) Client completes PoW and sends results in INTRO1 cell [INTRO1_POW]
4) Service verifies PoW and queues introduction based on PoW effort [SERVICE_VERIFY]
2.2. Proof-of-work overview
2.2.1. Primitives
For our proof-of-work scheme we want to minimize the spread of resources
between a motivated attacker and legitimate clients. This means that we are
looking to minimize any benefits that GPUs or ACICs can offer to an attacker.
For this reason we chose argon2 [REF_ARGON2] as the hash function for our
proof-of-work scheme since it's well audited and GPU-resistant and to some
extend ASIC-resistant as well.
As a password hash function, argon2 by default outputs 32 bytes of hash, and
takes as primary input a message and a nonce/salt. For the purposes of this
specification we will define an argon2() function as:
uint8_t hash_output[32] = argon2(uint8_t *message, uint8_t *nonce)'.
See section [ARGON_PARAMS] for more information on the secondary inputs of
argon2.
2.2.2. Dynamic PoW
DoS is a dynamic problem where the attacker's capabilities constantly change,
and hence we want our proof-of-work system to be dynamic and not stuck with a
static difficulty setting. Hence, instead of forcing clients to go below a
static target like in Bitcoin to be successful, we ask clients to "bid" using
their PoW effort. Effectively, a client gets higher priority the higher
effort they put into their proof-of-work. This is similar to how
proof-of-stake works but instead of staking coins, you stake work.
The benefit here is that legitimate clients who really care about getting
access can spend a big amount of effort into their PoW computation, which
should guarantee access to the service given reasonable adversary models. See
[POW_SECURITY] for more details about these guarantees and tradeoffs.
3. Protocol specification
3.1. Service encodes PoW parameters in descriptor [DESC_POW]
This whole protocol starts with the service encoding the PoW parameters in
the 'encrypted' (inner) part of the v3 descriptor. As follows:
"pow-params" SP type SP seed-b64 SP expiration-time NL
[At most once]
type: The type of PoW system used. We call the one specified here "v1"
seed-b64: A random seed that should be used as the input to the PoW
hash function. Should be 32 random bytes encoded in base64
without trailing padding.
expiration-time: A timestamp after which the above seed expires and is
no longer valid as the input for PoW. It's needed so
that the size of our replay cache does not grow
infinitely. It should be set to an hour in the future
(+- some randomness). {TODO: PARAM_TUNING}
{XXX: Expiration time makes us even more susceptible to clock skews, but
it's needed so that our replay cache refreshes. How to fix this?
See [CLIENT_BEHAVIOR] for more details.}
3.2. Client fetches descriptor and computes PoW [CLIENT_POW]
If a client receives a descriptor with "pow-params", it should assume that
the service is expecting a PoW input as part of the introduction protocol.
In such cases, the client should have been configured with a specific PoW
'target' (which is a 32-byte integer similar to the 'target' of Bitcoin
[REF_TARGET]). See [POW_SECURITY] for more information of how such a target
should be set. For the purposes of this section, we will assume that the
target has been set automatically by Tor, or the user configured it manually.
Now the client parses the descriptor and extracts the PoW parameters. It
makes sure that the expiration-time has not expired and if it has, it needs
to fetch a new descriptor.
To complete the PoW the client follows the following logic:
a) Client generates 'nonce' as 32 random bytes.
b) Client derives 'seed' by decoding 'seed-b64'.
c) Client computes hash_output = argon2(seed, nonce)
d) Client interprets hash_output as a 32-byte big-endian integer.
e) Client checks if int(hash_output) <= target.
e1) If yes, success! The client uses 'hash_output' as the hash and
'nonce' and 'seed' as its inputs.
e2) If no, fail! The client interprets 'nonce' as a big-endian integer,
increments it by one, and goes back to step (c).
At the end of the above procedure, the client should have a triplet
(hash_output, seed, nonce) that can be used as the answer to the PoW
puzzle. How quickly this happens depends solely on the 'target' parameter.
3.3. Client sends PoW in INTRO1 cell [INTRO1_POW]
Now that the client has an answer to the puzzle it's time to encode it into
an INTRODUCE1 cell. To do so the client adds an extension to the encrypted
portion of the INTRODUCE1 cell by using the EXTENSIONS field (see
[PROCESS_INTRO2] section in rend-spec-v3.txt). The encrypted portion of the
INTRODUCE1 cell only gets read by the onion service and is ignored by the
introduction point.
We propose a new EXT_FIELD_TYPE value:
[01] -- PROOF_OF_WORK
The EXT_FIELD content format is:
POW_VERSION [1 byte]
POW_SEED [32 bytes]
POW_NONCE [32 bytes]
POW_OUTPUT [32 bytes]
where:
POW_VERSION is 1 for the protocol specified in this proposal
POW_SEED is 'seed' from the section above
POW_NONCE is 'nonce' from the section above
POW_OUTPUT is 'hash_output' from the section above
{XXX: do we need POW_VERSION? Perhaps we can use EXT_FIELD_TYPE as version}
{XXX: do we need to encode the SEED? Perhaps we can ommit it since the
service already knows it. But what happens in cases of desynch, if client
has diff seed from service?}
{XXX: Do we need to include the output? Probably not. The service has to
compute it anyway during verification. What's the use?}
This will increase the INTRODUCE1 payload size by 99 bytes since the
extension type and length is 2 extra bytes, the N_EXTENSIONS field is always
present and currently set to 0 and the EXT_FIELD is 97 bytes. According to
ticket #33650, INTRODUCE1 cells currently have more than 200 bytes available.
3.4. Service verifies PoW and handles the introduction [SERVICE_VERIFY]
When a service receives an INTRODUCE1 with the PROOF_OF_WORK extension, it
should check its configuration on whether proof-of-work is required to
complete the introduction. If it's not required, the extension SHOULD BE
ignored. If it is required, the service follows the procedure detailed in
this section.
3.4.1. PoW verification
To verify the client's proof-of-work the service extracts (hash_output,
seed, nonce) from the INTRODUCE1 cell and MUST do the following steps:
1) Make sure that the client's seed is identical to the active seed.
2) Check the client's nonce for replays (see [REPLAY_PROTECTION] section).
3) Verify that 'hash_output =?= argon2(seed, nonce)
If any of these steps fail the service MUST ignore this introduction request
and abort the protocol.
If all the steps passed, then the circuit is added to the introduction queue
as detailed in section [INTRO_QUEUE].
3.4.1.1. Replay protection [REPLAY_PROTECTION]
The service MUST NOT accept introduction requests with the same (seed, nonce)
tuple. For this reason a replay protection mechanism must be employed.
The simplest way is to use a simple hash table to check whether a (seed,
nonce) tuple has been used before for the actiev duration of a
seed. Depending on how long a seed stays active this might be a viable
solution with reasonable memory/time overhead.
If there is a worry that we might get too many introductions during the
lifetime of a seed, we can use a Bloom filter as our replay cache
mechanism. The probabilistic nature of Bloom filters means that sometimes we
will flag some connections as replays even if they are not; with this false
positive probability increasing as the number of entries increase. However,
with the right parameter tuning this probability should be negligible and
well handled by clients. {TODO: PARAM_TUNING}
3.4.2. The Introduction Queue [INTRO_QUEUE]
3.4.2.1. Adding introductions to the introduction queue
When PoW is enabled and a verified introduction comes through, the service
instead of jumping straight into rendezvous, queues it and prioritizes it
based on how much effort was devoted by the client to PoW. This means that
introduction requests with high effort should be prioritized over those with
low effort.
To do so, the service maintains an "introduction priority queue" data
structure. Each element in that priority queue is an introduction request,
and its priority is the effort put into its PoW:
When a verified introduction comes through, the service interprets the PoW
hash as a 32-byte big-endian integer 'hash_int' and based on that integer it
inserts it into the right position of the priority_queue: The smallest
'hash_int' goes forward in the queue. If two elements have the same value,
the older one has priority over the newer one.
{XXX: Is this operation with 32-bytes integers expensive? How to make cheaper?}
{TODO: PARAM_TUNING: If the priority queue is only ordered based on the
effort what attacks can happen in various scenarios? Do we want to order on
time+effort? Which scenarios and attackers should we examine here?}
{TODO: PARAM_TUNING: What's the max size of the queue? How do we trim it? Can we
use WRED usefully?}
3.4.2.2. Handling introductions from the introduction queue [HANDLE_QUEUE]
The service should handle introductions by pulling from the introduction
queue.
Similar to how our cell scheduler works, the onion service subsystem will
poll the priority queue every 100ms tick and process the first 20 cells from
the priority queue (if they exist). The service will perform the rendezvous
and the rest of the onion service protocol as normal.
With this tempo, we can process 200 introduction cells per second.
{XXX: Is this good?}
{TODO: PARAM_TUNING: STRAWMAN: This needs hella tuning. Processing 20 cells
per 100ms is probably unmaintainable, since each cell is quite expensive:
doing so involving path selection, crypto and making circuits. We will need
to profile this procedure and see how we can do this scheduling better.}
{XXX: This might be a nice place to promote multithreading. Queues and pools
are nice objects to do multithreading since you can have multiple threads
pull from the queue, or leave stuff on the queue. Not sure if this should be
in the proposal tho.}
4. Attacker strategies [ATTACK_META]
Now that we defined our protocol we need to start tweaking the various
knobs. But before we can do that, we first need to understand a few
high-level attacker strategies to see what we are fighting against.
4.1.1. Total overwhelm strat
Given the way the introduction queue works (see [HANDLE_QUEUE]), a very
effective strategy for the attacker is to totally overwhelm the queue
processing by sending more high-effort introductions than the onion service
can handle at any given tick.
To do so, the attacker would have to send at least 20 high-effort
introduction cells every 100ms, where high-effort is a PoW which is above the
estimated level of "the motivated user" (see [USER_MODEL]).
An easier attack for the adversary, is the same strategy but with
introduction cells that are all above the comfortable level of "the standard
user" (see [USER_MODEL]). This would block out all standard users and only
allow motivated users to pass.
{XXX: What other attack strategies we should care about?}
5. Parameter tuning [POW_SECURITY]
There are various parameters in this system that need to be tuned.
We will first start by tuning the default difficulty of our PoW
system. That's gonna define an expected time for attackers and clients to
succeed.
We are then gonna tune the parameters of the argon2 hash function. That will
define the resources that an attacker needs to spend to overwhelm the onion
service, the resources that the service needs to spend to verify introduction
requests, and the resources that legitimate clients need to spend to get to
the onon service.
5.1. PoW Difficulty settings
The difficulty setting of our PoW basically dictates how difficult it should
be to get a success in our PoW system. In classic PoW systems, "success" is
defined as getting a hash output below the "target". However, since our
system is dynamic, we define "success" as an abstract high-effort computation.
Even tho our system is dynamic, we still need default difficulty settings
that will define the metagame. The client and attacker can still aim higher
or lower, but for UX purposes and for analysis purposes we do need to define
some difficulties.
We hence created the table (see [REF_TABLE]) below which shows how much time
a legitimate client with a single machine should expect to burn before they
get a single success. The x-axis is how many successes we want the attacker
to be able to do per second: the more successes we allow the adversary, the
more they can overwhelm our introduction queue. The y-axis is how many
machines the adversary has in her disposal, ranging from just 5 to 1000.
===============================================================
| Expected Time (in seconds) Per Success For One Machine |
===========================================================================
| |
| Attacker Succeses 1 5 10 20 30 50 |
| per second |
| |
| 5 5 1 0 0 0 0 |
| 50 50 10 5 2 1 1 |
| 100 100 20 10 5 3 2 |
| Attacker 200 200 40 20 10 6 4 |
| Boxes 300 300 60 30 15 10 6 |
| 400 400 80 40 20 13 8 |
| 500 500 100 50 25 16 10 |
| 1000 1000 200 100 50 33 20 |
| |
============================================================================
Here is how you can read the table above:
- If an adversary has a botnet with 1000 boxes, and we want to limit her to 1
success per second, then a legitimate client with a single box should be
expected to spend 1000 seconds getting a single success.
- If an adversary has a botnet with 1000 boxes, and we want to limit her to 5
successes per second, then a legitimate client with a single box should be
expected to spend 200 seconds getting a single success.
- If an adversary has a botnet with 500 boxes, and we want to limit her to 5
successes per second, then a legitimate client with a single box should be
expected to spend 100 seconds getting a single success.
- If an adversary has access to 50 boxes, and we want to limit her to 5
successes per second, then a legitimate client with a single box should be
expected to spend 10 seconds getting a single success.
- If an adversary has access to 5 boxes, and we want to limit her to 5
successes per second, then a legitimate client with a single box should be
expected to spend 1 seconds getting a single success.
With the above table we can create some profiles for default values of our
PoW difficulty. So for example, we can use the last case as the default
parameter for Tor Browser, and then create three more profiles for more
expensive cases, scaling up to the first case which could be hardest since
the client is expected to spend 15 minutes for a single introduction.
{TODO: PARAM_TUNING You can see that this section is completely CPU/memory
agnostic, and it does not take into account potential optimizations that can
come from GPU/ASICs. This is intentional so that we don't put more variables
into this equation right now, but as this proposal moves forward we will need
to put more concrete values here.}
5.2. Argon2 parameters [ARGON_PARAMS]
We now need to define the secondary argon2 parameters as defined in
[REF_ARGON2]. This includes the number of lanes 'h', the memory size 'm', the
number of iterations 't'. Section 9 of [REF_ARGON2] recommends an approach of
how to tune these parameters.
To tune these parameters we are looking to *minimize* the verification speed
of an onion service, while *maximizing* the sparse resources spent by an
adversary trying to overwhelm the service using [ATTACK_META].
When it comes to verification speed, to verify a single introduction cell the
service needs to do a single argon2 call: so the service will need to do
hundreds of those per second as INTRODUCE2 cells arrive. The service will
have to do this verification step even for very cheap zero-effort PoW
received, so this has to be a cheap procedure so that it doesn't become a DoS
vector of each own. Hence each individual argon2 call must be cheap enough to
be able to be done comfortably and plentifuly by an onion service with a
single host (or horizontally scaled with Onionbalance).
At the same time, the adversary will have to do thousands of these calls if
she wants to make high-effort PoW, so it's this assymetry that we are looking
to exploit here. Right now, the most expensive resource for adversaries is
the RAM size, and that's why we chose argon2 which is memory-hard.
To minmax this game we will need
{TODO: PARAM_TUNING: I've had a hard time minmaxing this game for
argon2. Even argon2 invocations with a small memory parameter will take
multiple milliseconds to run on my machine, and the parameters recommended in
section 8 of the paper all take many hundreds of milliseconds. This is just
not practical for our use case, since we want to process hundreds of such PoW
per second... I also did not manage to find a benchmark of argon2 calls for
different CPU/GPU/FPGA configurations.}
5. Client behavior [CLIENT_BEHAVIOR]
This proposal introduces a bunch of new ways where a legitimate client can
fail to reach the onion service.
Furthermore, there is currently no end-to-end way for the onion service to
inform the client that the introduction failed. The INTRO_ACK cell is not
end-to-end (it's from the introduction point to the client) and hence it does
not allow the service to inform the client that the rendezvous is never gonna
occur.
Let's examine a few such cases:
5.1. Timeout issues
Alice can fail to reach the onion service if her introduction request falls
off the priority queue, or if the priority queue is so big that the
connection times out.
Is building a new introduction circuit sufficient here? Or do we need to
build an end-to-end mechanism over the introduction circuit to inform
her? {XXX}
How should timeout values change here since the priority queue will cause
bigger delays than usual to rendezvous? Can there be some feedback mechanism
to inform the client of its queue position or ETA?
5.2. Seed expiration issues
As mentioned in [DESC_POW], the expiration timestamp on the PoW seed can
cause issues with clock skewed clients. Furthermore, even not clock skewed
clients can encounter TOCTOU-style race conditions here.
How should this be handled? Should we have multiple active seeds at the same
time similar to how we have overlapping descriptors and time periods in v3?
This would solve the problem but it grows the complexity of the system
substantially. {XXX}
5.3. Other descriptor issues
Another race condition here is if the service enables PoW, while a client has
a cached descriptor. How will the client notice that PoW is needed? Does it
need to fetch a new descriptor? Should there be another feedback mechanism?
{XXX}
5. Discussion
5.1. UX
This proposal has user facing UX consequences. Here are a few UX approaches
with increasing engineering difficulty:
a) Tor Browser needs a "range field" which the user can use to specify how
much effort they want to spend in PoW if this ever occurs while they are
browsing. The ranges could be from "Easy" to "Difficult", or we could try
to estimate time using an average computer. This setting is in the Tor
Browser settings and users need to find it.
b) We start with a default effort setting, and then we use the new onion
errors (see #19251) to estimate when an onion service connection has
failed because of DoS, and only then we present the user a "range field"
which they can set dynamically. Detecting when an onion service connection
has failed because of DoS can be hard because of the lack of feedback (see
[CLIENT_BEHAVIOR])
c) We start with a default effort setting, and if things fail we
automatically try to figure out an effort setting that will work for the
user by doing some trial-and-error connections with different effort
values. Until the connection succeeds we present a "Service is
overwhelmed, please wait" message to the user.
For this proposal to work initially we need at least (a), and then we can
start thinking of how far we want to take it.
5.2. Future directions [FUTURE_WORK]
This is just the beginning in DoS defences for Tor and there are various
future avenues that we can investigate. Here is a brief summary of these:
"More advanced PoW schemes" -- We could use more advanced memory-hard PoW
schemes like MTP-argon2 or Itsuku to make it even harder for
adversaries to create successful PoWs. Unfortunately these schemes
have much bigger proof sizes, and they won't fit in INTRODUCE1 cells.
See #31223 for more details.
"Third-party anonymous credentials" -- We can use anonymous credentials and a
third-party token issuance server on the clearnet to issue tokens
based on PoW or CAPTCHA and then use those tokens to get access to the
service. See [REF_CREDS] for more details.
"PoW + Anonymous Credentials" -- We can make a hybrid of the above ideas
where we present a hard puzzle to the user when connecting to the
onion service, and if they solve it we then give the user a bunch of
anonymous tokens that can be used in the future. This can all happen
between the client and the service without a need for a third party.
All of the above approaches are much more complicated than this proposal, and
hence we want to start easy before we get into more serious projects.
5.3. Environment
We love the environment! We are concerned of how PoW schemes can waste energy
by doing useless hash iterations. Here is a few reasons we still decided to
pursue a PoW approach here:
"We are not making things worse" -- DoS attacks are already happening and
attackers are already burning energy to carry them out both on the
attacker side, on the service side and on the network side. We think that
asking legitimate clients to carry out PoW computations is not gonna
affect the equation too much, since an attacker right now can very
quickly cause the same damage that hundreds of legitimate clients do a
whole day.
"We hope to make things better" -- The hope is that proposals like this will
make the DoS actors go away and hence the PoW system will not be used. As
long as DoS is happening there will be a waste of energy, but if we
manage to demotivate them with technical means, the network as a whole
will less wasteful. Also see [CATCH22] for a similar argument.
6. References
[REF_ARGON2]: https://github.com/P-H-C/phc-winner-argon2/blob/master/argon2-specs.pdf
https://password-hashing.net/#argon2
[REF_TABLE]: The table is based on the script below plus some manual editing for readability:
https://gist.github.com/asn-d6/99a936b0467b0cef88a677baaf0bbd04
[REF_BOTNET]: https://media.kasperskycontenthub.com/wp-content/uploads/sites/43/2009/07/01121538/ynam_botnets_0907_en.pdf
[REF_CREDS]: https://lists.torproject.org/pipermail/tor-dev/2020-March/014198.html
[REF_TARGET]: https://en.bitcoin.it/wiki/Target
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