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GHSA-w7vc-732c-9m39

MEDIUM

GHSA-w7vc-732c-9m39 is a medium-severity (CVSS 5.3) Uncontrolled Resource Consumption vulnerability in pyjwt. O3 Security confirms whether GHSA-w7vc-732c-9m39 is actually reachable in your code before you act, and blocks exploitation at runtime until you patch.

PyJWT: Unauthenticated DoS via unbounded Base64URL decoding of unused payload segment in b64=false detached JWS

Also known asCVE-2026-48525PYSEC-2026-178
Published
Jun 15, 2026
Updated
Jun 16, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 4, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

EPSS Exploitation Probability

via FIRST.org ↗
0.4%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs30th percentile — riskier than 30% of all scored CVEsHighest risk
0.00%0.29%0.58%0.87%0.0%0.3%0.4%0.4%0.4%Jun 26Aug 26Sep 26

EPSS (Exploit Prediction Scoring System) is a daily probability model maintained by FIRST.org. It estimates the likelihood a CVE will be exploited in production environments within the next 30 days, derived from real-world threat intelligence signals.

How urgent is this, really

GHSA-w7vc-732c-9m39 plotted by exploitation likelihood (EPSS) against impact (CVSS). The shaded corner — EPSS 50%+ and CVSS 7.0+ — is where this CVE doesn't sit, though severity or exploitability alone can still warrant action.

Where this sits among everything scored

Of 0 CVEs with a current EPSS score, this one falls in the < 10% band (highlighted). Real counts from FIRST.org, not a sample — log-scaled since the landscape is heavily right-skewed.

Real-World Exposure

1 pkg affected
🐍pyjwt

Real-time download stats are indexed for npm and PyPI packages. This vulnerability affects PyPI packages — download data is not available via public APIs for these ecosystems.

Description

[!NOTE] Practical impact depends on whether request body-size limits are enforced upstream (proxy/web-server/framework). Deployments with typical body-size caps (≤2 MB) bound the amplifier significantly; deployments accepting larger token inputs are more exposed.

When verifying detached JWS tokens using the unencoded-payload option ("b64": false, RFC 7797), PyJWT performs Base64URL decoding of the compact-serialization payload segment before enforcing the detached-payload rules.

For b64=false, PyJWT later discards that decoded payload and replaces it with the caller-provided detached_payload. In practice, this turns the middle segment into an attacker-controlled “work amplifier”: a remote client can supply an arbitrarily large Base64URL payload segment that forces CPU work + memory allocations even if the signature is invalid.

This creates an unauthenticated DoS vector against any endpoint that verifies detached JWS using PyJWT.


Affected Component(s)

  • jwt/api_jws.py

    • PyJWS.decode() / PyJWS.decode_complete()
    • _load() (parsing and Base64URL decoding)

Root Cause (exact logic flaw)

What happens in the code

In jwt/api_jws.py, decode_complete() does the following (order matters):

  • Calls _load(jwt) first, which decodes the token segments
  • Only after that, checks header.get("b64") and if False, it replaces payload = detached_payload and rebuilds the signing input

This behavior is visible in decode_complete():

  • _load(jwt) happens before the b64=false handling
  • then payload = detached_payload and signing_input = ... detached_payload happens afterward ([GitHub][1])

Inside _load(), PyJWT unconditionally performs:

  • payload = base64url_decode(payload_segment) This is the expensive step the attacker can amplify ([GitHub][1])

Why this becomes a vulnerability

For b64=false detached JWS, the payload segment in compact form is effectively not needed for verification in PyJWT’s own logic (since the library uses detached_payload as the real payload). Yet PyJWT still decodes it first, meaning:

  • cost is paid even when signature is invalid
  • the decoded bytes are discarded
  • attacker controls the size of this cost via token length

Impact (evidence-driven)

Security impact

  • Unauthenticated remote DoS: decoding work happens before signature rejection → attacker does not need signing key.
  • CPU amplification: Base64URL decode time scales linearly with payload segment size.
  • Memory amplification: decoded output allocates large byte buffers (tens of MB per request).
  • Operational impact: request queueing / worker starvation under modest concurrency bursts.

Standards context (RFC 7797)

RFC 7797 explicitly notes this option is used when payload is large and/or detached, and discusses interoperability requirements around marking it critical (“crit” with “b64”). ([IETF Datatracker][2]) (PyJWT supports crit validation, but the issue here is decode order / unbounded decode of an unused segment.)


Affected Versions

  • Confirmed affected: PyJWT 2.12.1 (tested from your local editable install and repo).
  • Likely affected: all versions that include detached payload support for JWS decoding, which was introduced in 2.4.0 (“Add detached payload support for JWS encoding and decoding”). ([pyjwt.readthedocs.io][3])

(For GHSA, this phrasing is strong: “confirmed” + “likely since feature introduction”.)


Threat Model

Typical real deployment

A service verifies signed HTTP requests or webhooks using detached JWS:

  • token is provided in JSON body / query / header
  • actual payload is the HTTP request body passed as detached_payload

Attacker

  • remote unauthenticated client
  • can send requests to verify endpoint
  • does not need a valid signature (invalid signature still triggers the expensive decode path)

Attack chain

  1. Attacker crafts a JWS compact token with header containing "b64": false and crit:["b64"].
  2. Attacker inflates the payload segment (middle segment) to millions of Base64URL characters.
  3. Server calls PyJWS.decode(...detached_payload=...).
  4. PyJWT decodes the inflated segment (CPU + memory).
  5. Signature is rejected afterward (401) — but resources already consumed.
  6. Repeated requests or bursts cause queueing/worker starvation → DoS.

Proof of Concept - file names + results

PoC placement


PoC # 1 - Localhost verification server

File: server_localhost.py

Purpose: real HTTP endpoint (POST /verify) that calls PyJWT detached verification and prints: ok / time_ms / peak_bytes / token_len / error.

Results (server console output)

[+] Listening on http://127.0.0.1:8000
[+] POST /verify  JSON: {"token": "..."}

[127.0.0.1] ok=True  time_ms=0.102 peak_bytes=2624     token_len=117      err=None
[127.0.0.1] ok=False time_ms=2.012 peak_bytes=2000983  token_len=500078   err=InvalidSignatureError
[127.0.0.1] ok=True  time_ms=1.591 peak_bytes=2001061  token_len=500117   err=None

[127.0.0.1] ok=True  time_ms=0.065 peak_bytes=2304     token_len=117      err=None
[127.0.0.1] ok=False time_ms=7.534 peak_bytes=8000983  token_len=2000078  err=InvalidSignatureError
[127.0.0.1] ok=True  time_ms=6.347 peak_bytes=8001061  token_len=2000117  err=None

[127.0.0.1] ok=True  time_ms=0.066 peak_bytes=2304     token_len=117      err=None
[127.0.0.1] ok=False time_ms=23.034 peak_bytes=32000983 token_len=8000078 err=InvalidSignatureError
[127.0.0.1] ok=True  time_ms=22.097 peak_bytes=32001061 token_len=8000117 err=None

Key takeaways from these results

  • At 8,000,000 chars, a single invalid-signature request still causes:

    • ~23 ms server work
    • ~32 MB peak allocations
    • returns 401 (invalid signature) → attacker does not need key.

PoC # 2 - Localhost network client

File: client_localhost.py Purpose: generates baseline + (invalid signature) + (valid signature) tokens and sends them over HTTP to localhost server.

Results (client output)

payload-chars = 500,000

=== BASELINE (valid b64=false token) ===
HTTP: 200
client_wall_ms: 6.3499...
server_time_ms: 0.10197...
server_peak_bytes: 2624

=== ATTACK (INVALID signature - attacker needs no key) ===
HTTP: 401
client_wall_ms: 4.1010...
server_time_ms: 2.01217...
server_peak_bytes: 2000983
error: InvalidSignatureError

=== ATTACK (VALID signature - accepted path still wastes) ===
HTTP: 200
client_wall_ms: 3.6586...
server_time_ms: 1.59092...
server_peak_bytes: 2001061

payload-chars = 2,000,000

=== BASELINE ===
HTTP: 200
server_time_ms: 0.06527...
server_peak_bytes: 2304

=== ATTACK (INVALID signature) ===
HTTP: 401
server_time_ms: 7.53430...
server_peak_bytes: 8000983

=== ATTACK (VALID signature) ===
HTTP: 200
server_time_ms: 6.34682...
server_peak_bytes: 8001061

payload-chars = 8,000,000

=== BASELINE ===
HTTP: 200
server_time_ms: 0.06573...
server_peak_bytes: 2304

=== ATTACK (INVALID signature) ===
HTTP: 401
server_time_ms: 23.03403...
server_peak_bytes: 32000983

=== ATTACK (VALID signature) ===
HTTP: 200
server_time_ms: 22.09702...
server_peak_bytes: 32001061

Why this is strong evidence

  • The server clearly does heavy work before rejecting invalid signatures.
  • The “valid signature” case shows even accepted requests waste resources due to unused payload segment.

PoC # 3 - Localhost flood / burst concurrency

File: flood_localhost.py Purpose: sends N concurrent invalid-signature requests over HTTP to demonstrate queueing/worker starvation.

Results (your run: 20 concurrent @ 8,000,000 chars)

total_wall_ms: 1374.5405770000616

(16, 401, 1156.4504789998864, 21.350951999920653, 32000983, 'InvalidSignatureError')
(19, 401, 1151.2852699997893, 21.208721999755653, 32000983, 'InvalidSignatureError')
(18, 401, 1102.7211239997996, 21.685218999664357, 32000983, 'InvalidSignatureError')
(13, 401, 1102.0718189997751, 21.26572200040755, 32000983, 'InvalidSignatureError')
(11, 401, 1095.9345460000804, 20.586017000368884, 32000983, 'InvalidSignatureError')
(17, 401, 1085.2552810001725, 22.893039000337012, 32000983, 'InvalidSignatureError')
(10, 401, 1078.3629560000918, 22.737160999895423, 32000983, 'InvalidSignatureError')
(7,  401, 1048.2011740000416, 22.476282000297942, 32000983, 'InvalidSignatureError')
(8,  401, 378.93017700025666, 21.377330999712285, 32000983, 'InvalidSignatureError')
(1,  401, 281.45106800002395, 21.34223099983501, 32000983, 'InvalidSignatureError')

Interpretation

  • Each request still costs ~20–23 ms server processing and ~32 MB peak allocations.
  • But client-observed latency rises up to ~1.15 seconds because requests queue behind each other → clear worker starvation/HoL blocking.
  • All were rejected with 401 InvalidSignatureError → still unauthenticated.

Fix

Goal

Prevent unbounded resource consumption from an attacker-controlled payload segment that is unused in b64=false detached flow.

Minimal change strategy

In _load() (or by refactoring parse order), do not Base64-decode payload_segment until after you know whether b64=false applies.

Two safe options:

  1. Reject non-empty payload segment when b64=false

    • Parse header first
    • If b64 is false and payload_segment is non-empty → raise DecodeError before decoding
    • Then verification uses detached_payload only
  2. Skip decoding payload segment entirely when b64=false

    • Keep payload segment as raw bytes or empty
    • Use detached payload for signing input

This aligns with the idea that detached payload is the trusted payload input for verification; the compact payload segment should not become a resource amplification vector.

(Implementation context: the current decode order and unconditional base64url_decode(payload_segment) are visible in the file and line region around _load() and decode_complete() ([GitHub][1]).)


Workarounds

  • Enforce strict max token length at the HTTP boundary (proxy/gateway).
  • Apply rate limiting on verification endpoints.
  • If detached JWS (b64=false) is not needed in your app, reject tokens where header includes "b64": false.

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIpyjwt2.8.0&&< 2.13.02.13.0

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for pyjwt. O3's reachability analysis confirms whether the vulnerable code path is actually invoked in your application, so you act on real exposure instead of every transitive match.

  2. Fix

    Update pyjwt to 2.13.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-w7vc-732c-9m39 is resolved across your whole dependency graph.

  3. Workarounds

    If you can't upgrade right away: gate or disable the affected feature, validate untrusted input at the boundary, and avoid passing attacker-controlled data into the vulnerable path. O3's runtime protection blocks exploitation in production as an interim safeguard until the upgrade lands.

  4. How O3 protects you

    O3 pinpoints whether GHSA-w7vc-732c-9m39 is reachable in your code and exactly where to fix it, then blocks exploitation in production at runtime until the patched version is deployed.

Tailored to GHSA-w7vc-732c-9m39. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

> [!NOTE] > Practical impact depends on whether request body-size limits are enforced upstream (proxy/web-server/framework). Deployments with typical body-size caps (≤2 MB) bound the amplifier significantly; deployments accepting larger token inputs are more exposed. When verifying detached JWS tokens using the unencoded-payload option (`"b64": false`, RFC 7797), PyJWT performs **Base64URL decoding of the compact-serialization payload segment** *before* enforcing the detached-payload rules. For `b64=false`, PyJWT later **discards** that decoded payload and replaces it with the caller-provide
O3 Security · Impact-Aware SCA

Is GHSA-w7vc-732c-9m39 in your dependencies?

O3 detects GHSA-w7vc-732c-9m39 across PyPI dependencies and uses function-level reachability to confirm whether the vulnerable code path is actually reachable — not just present. No false positives.

GHSA-w7vc-732c-9m39: pyjwt Denial of… | O3 Security