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GHSA-hf2g-6j7h-98wg CVE-2026-52879 GO-2026-5424

klever-go: Unbounded goroutine spawn on direct-message ingress enables peer-driven DoS

High Go
Severity
7.5 / 10
High · CVSS 3.1
Exploit chance (EPSS)
0.49%
Chance of exploitation in the next 30 days. Higher than 42.02% of scored vulnerabilities.
Known exploited
No
Not in CISA's catalog
Weakness
CWE-400 Uncontrolled Resource Consumption
CWE-770 Allocation of Resources Without Limits or Throttling
Fix
1.7.18
Upgrade github.com/klever-io/klever-go to this version or later

Description

Summary

networkMessenger.directMessageHandler in network/p2p/libp2p/netMessenger.go spawns a fresh goroutine for every incoming direct message before the antiflood layer makes an admission decision. There is no semaphore, throttler, or bound on concurrent in-flight spawns.

A single connected libp2p peer can open a DirectSendID stream and send well-formed TopicMessage envelopes with varying sequence numbers. Each accepted direct message reaches directMessageHandler and triggers a fresh goroutine before processor.ProcessReceivedMessage runs. This allows unbounded goroutine growth and node availability degradation from one peer.

This remains present in the latest release v1.7.17: network/p2p/libp2p/netMessenger.go:1060 still spawns go func(msg p2p.MessageP2P) before processor.ProcessReceivedMessage. I also verified current develop commit 10bcfd50, where the same spawn remains at network/p2p/libp2p/netMessenger.go:1115.

This is distinct from GHSA-74m6-4hjp-7226 and GHSA-87m7-qffr-542v. Those advisories concern MultiDataInterceptor decompression/throttler behavior. This report concerns the libp2p direct-message ingress wrapper spawning an unbounded goroutine before processor-level antiflood/admission logic runs. A patch to Batch.Decompress or MultiDataInterceptor does not bound this direct-message goroutine spawn.

Details

The affected path is network/p2p/libp2p/netMessenger.go in directMessageHandler.

The direct-message path transforms and validates the message, looks up the topic processor, then immediately spawns a goroutine:

func (netMes *networkMessenger) directMessageHandler(message *pubsub.Message, fromConnectedPeer core.PeerID) error {
    var processor p2p.MessageProcessor

    topic := *message.Topic
    msg, err := netMes.transformAndCheckMessage(message, fromConnectedPeer, topic)
    if err != nil {
        return err
    }

    netMes.mutTopics.RLock()
    processor = netMes.processors[topic]
    netMes.mutTopics.RUnlock()

    if processor == nil {
        return fmt.Errorf("%w on directMessageHandler for topic %s", p2p.ErrNilValidator, topic)
    }

    go func(msg p2p.MessageP2P) {
        if check.IfNil(msg) {
            return
        }

        errProcess := processor.ProcessReceivedMessage(msg, fromConnectedPeer)
        // ...
    }(msg)

    return nil
}

The processor-level antiflood decision happens inside ProcessReceivedMessage, after the goroutine, its stack, and the cloned message reference already exist. That means antiflood can bound processing rate, but not goroutine creation rate.

The existing goRoutinesThrottler with capacity broadcastGoRoutines = 1000 is wired into outgoing broadcast paths such as BroadcastOnChannelBlocking, not this incoming direct-message path.

The parallel pubsub ingress path in the same file handles a comparable inbound message surface synchronously:

err = handler.ProcessReceivedMessage(msg, fromConnectedPeer)

So the direct-message path is asymmetric: same transform/check function, same ProcessReceivedMessage callee, but direct-message ingress adds an unbounded goroutine spawn.

Reachability:

  • directSender.go registers DirectSendID as a libp2p stream protocol.
  • directStreamHandler reads framed pubsub.Message envelopes from the stream.
  • directStreamHandler forwards each message to networkMessenger.directMessageHandler.
  • Any connected peer can send well-formed envelopes to registered topics.
  • The seenMessages cache keys on From + Seqno; Seqno is attacker-controlled in the envelope, so incrementing it bypasses dedupe.

PoC

GitHub Private Vulnerability Reporting does not appear to allow file attachments in this form, so I am including the reproduction command and captured output inline. I can provide the full Go test file immediately if useful.

The PoC is a Go test file intended to be placed under network/p2p/libp2p/ in a klever-go checkout. It exercises the real network/p2p/libp2p package with NewMockMessenger.

Reproduction:

git clone https://github.com/klever-io/klever-go
cd klever-go
git checkout v1.7.16

# Place dos_directmsg_test.go into:
# network/p2p/libp2p/

go test ./network/p2p/libp2p/ -run TestPoC_ -count=1 -v -timeout 60s

Captured output:

=== RUN   TestPoC_DirectMessageHandler_SpawnsGoroutinePerMessage
    baseline goroutines: 43
    peak goroutines after 500 direct messages: 543 (delta = 500)
    final goroutines after drain + GC: 43
POC_RESULT direct=spawn N=500 baseline=43 peak=543 delta=500 threshold=400 final=43
--- PASS

=== RUN   TestPoC_SynchronousHandler_NoGoroutineGrowth
    baseline goroutines: 47
    peak goroutines after 500 synchronous calls: 47 (delta = 0)
POC_RESULT sync=block N=500 baseline=47 peak=47 delta=0
--- PASS

=== RUN   TestPoC_DirectMessageHandler_NoThrottlerInPath
    all 2000 SendToConnectedPeer calls returned in 2.490708ms -- no throttler blocking
POC_RESULT throttler=absent N=2000 elapsed=2.490708ms
--- PASS

Reading:

  1. 500 direct messages with slow processors produced exactly 500 new goroutines.
  2. The synchronous control path produced zero goroutine growth.
  3. 2000 messages, twice the outgoing broadcastGoRoutines = 1000 capacity, returned immediately, showing no ingress throttler blocks this path.

Impact

A single connected peer can sustain unbounded goroutine spawn growth on a klever-go node. Each spawned goroutine allocates its own stack, holds message references until the processor returns, and adds scheduler and GC pressure before antiflood admission can reject the message.

Under realistic attacker line rate and non-trivial processor latency, goroutine count can grow faster than the runtime drains it, degrading the node's ability to process legitimate traffic. This maps to the SECURITY.md High category: "Denial of Service affecting network availability."

All testing was local only. I did not contact Klever mainnet, public testnet, hosted RPCs, explorers, or third-party production infrastructure.

Suggested fixes:

  1. Wire goRoutinesThrottler.CanProcess() or a dedicated ingress throttler before the go func() spawn in directMessageHandler.
  2. Or remove the goroutine and call ProcessReceivedMessage synchronously, matching the existing pubsubCallback path.

Disclosure note: I originally sent this report to security@klever.org on 2026-05-13. Since SECURITY.md lists GitHub Private Vulnerability Reporting as the recommended channel, I am resubmitting it here.

Affected versions

Go

PackageVulnerableFixed in
github.com/klever-io/klever-go
>= 1.7.14, < 1.7.18
1.7.18

How to fix

Move to the fixed version or later with your package manager, update the lockfile, and run your tests. If the package only arrives through another dependency, upgrade that dependency first. If none of its releases pulls a fixed version yet, force the version with your package manager's override.

github.com/klever-io/klever-go Go → 1.7.18

go
go get github.com/klever-io/klever-go@v1.7.18 && go mod tidy

Severity breakdown

CVSS 3.1 7.5

CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H

Attack vector
Network
Attack complexity
Low
Privileges required
None
User interaction
None
Scope
Unchanged
Confidentiality
None
Integrity
None
Availability
High

Weakness

CWE-400: Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource.

How to prevent it
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, or uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution is simply difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply makes the attack require more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Implementation: Ensure that all failures in resource allocation place the system into a safe posture.

CWE-770: Allocation of Resources Without Limits or Throttling

The product allocates a reusable resource or group of resources on behalf of an actor without imposing any intended restrictions on the size or number of resources that can be allocated.

How to prevent it
  • Requirements: Clearly specify the minimum and maximum expectations for capabilities, and dictate which behaviors are acceptable when resource allocation reaches limits.
  • Architecture and Design: Limit the amount of resources that are accessible to unprivileged users. Set per-user limits for resources. Allow the system administrator to define these limits. Be careful to avoid CWE-410.
  • Architecture and Design: Design throttling mechanisms into the system architecture. The best protection is to limit the amount of resources that an unauthorized user can cause to be expended. A strong authentication and access control model will help prevent such attacks from occurring in the first place, and it will help the administrator to identify who is committing the abuse. The login application should be protected against DoS attacks as much as possible. Limiting the database access, perhaps by caching result sets, can help minimize the resources expended. To further limit the potential for a DoS attack, consider tracking the rate of requests received from users and blocking requests that exceed a defined rate threshold.
  • Implementation: Assume all input is malicious. Use an "accept known good" input validation strategy, i.e., use a list of acceptable inputs that strictly conform to specifications. Reject any input that does not strictly conform to specifications, or transform it into something that does. When performing input validation, consider all potentially relevant properties, including length, type of input, the full range of acceptable values, missing or extra inputs, syntax, consistency across related fields, and conformance to business rules. As an example of business rule logic, "boat" may be syntactically valid because it only contains alphanumeric characters, but it is not valid if the input is only expected to contain colors such as "red" or "blue." Do not rely exclusively on looking for malicious or malformed inputs. This is likely to miss at least one undesirable input, especially if the code's environment changes. This can give attackers enough room to bypass the intended validation. However, denylists can be useful for detecting potential attacks or determining which inputs are so malformed that they should be rejected outright.
  • Architecture and Design: For any security checks that are performed on the client side, ensure that these checks are duplicated on the server side, in order to avoid CWE-602. Attackers can bypass the client-side checks by modifying values after the checks have been performed, or by changing the client to remove the client-side checks entirely. Then, these modified values would be submitted to the server.
  • Architecture and Design: Mitigation of resource exhaustion attacks requires that the target system either: recognizes the attack and denies that user further access for a given amount of time, typically by using increasing time delays uniformly throttles all requests in order to make it more difficult to consume resources more quickly than they can again be freed. The first of these solutions is an issue in itself though, since it may allow attackers to prevent the use of the system by a particular valid user. If the attacker impersonates the valid user, they may be able to prevent the user from accessing the server in question. The second solution can be difficult to effectively institute -- and even when properly done, it does not provide a full solution. It simply requires more resources on the part of the attacker.
  • Architecture and Design: Ensure that protocols have specific limits of scale placed on them.
  • Architecture and Design, Implementation: If the program must fail, ensure that it fails gracefully (fails closed). There may be a temptation to simply let the program fail poorly in cases such as low memory conditions, but an attacker may be able to assert control before the software has fully exited. Alternately, an uncontrolled failure could cause cascading problems with other downstream components; for example, the program could send a signal to a downstream process so the process immediately knows that a problem has occurred and has a better chance of recovery. Ensure that all failures in resource allocation place the system into a safe posture.
  • Operation, Architecture and Design: Use quotas or other resource-limiting settings provided by the operating system or environment. For example, when managing system resources in POSIX, setrlimit() can be used to set limits for certain types of resources, and getrlimit() can determine how many resources are available. However, these functions are not available on all operating systems. When the current levels get close to the maximum that is defined for the application (see CWE-770), then limit the allocation of further resources to privileged users; alternately, begin releasing resources for less-privileged users. While this mitigation may protect the system from attack, it will not necessarily stop attackers from adversely impacting other users. Ensure that the application performs the appropriate error checks and error handling in case resources become unavailable (CWE-703).

References

Timeline

  1. Published
  2. Last updated by the source
  3. Latest EPSS score
AdvisorySeverityWhy it's related
GHSA-7c7c-373r-gfjj
Klever-Go: Elasticsearch bulk / painless injection via on-chain account name -> explorer/indexer data forgery
High Also affects github.com/klever-io/klever-go
GHSA-9wh6-9hq7-9688
Klever-Go: Validator registration accepts an unvalidated BLS public key → consensus liveness DoS
High Also affects github.com/klever-io/klever-go
GHSA-26r5-4mm2-px5c
Klever-Go: Zombie-order theft: `Buy` missing `IsClaimed` guard in native marketplace
High Also affects github.com/klever-io/klever-go
GHSA-97cv-x867-6xhm
Klever-Go Account takeover: `kleverUpdateAccountPermission` authorizes on attacker-controlled `RecipientAddr` instead of the authenticated caller
High Also affects github.com/klever-io/klever-go
GHSA-4fwh-wrm6-97xm
Klever-Go: Unauthenticated WebSocket /subscribe: no read-size limit, no connection cap, permissive origin -> remote node memory/goroutine exhaustion (DoS)
High Also affects github.com/klever-io/klever-go
GHSA-9v8p-frvj-2pcm
Klever-Go: /log controls global node logging
High Also affects github.com/klever-io/klever-go
GHSA-mrpp-v6pg-p54x
klever-go: SFT add-quantity `int64` overflow bypasses a finite per-nonce MaxSupply
High Also affects github.com/klever-io/klever-go
GHSA-v358-wf77-39xv
klever-go: Percentage-transfer royalty skips the source debit at exactly-100% splits
High Also affects github.com/klever-io/klever-go
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