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MEDIUM severity

CVE-2026-27695 — zae-limiter

MEDIUMFix: zeroae/zae-limiter@481ce44

CVE-2026-27695 is a medium-severity (CVSS 4.3) CWE-770 vulnerability in zae-limiter. A fix is available for zae-limiter — see the affected versions and patch details below.

zae-limiter: DynamoDB hot partition throttling enables per-entity Denial of Service

Also known asGHSA-76rv-2r9v-c5m6PYSEC-2026-3434
Published
Feb 25, 2026
Updated
Aug 12, 2026
Affected
1 pkg
Patched
1 / 1
Exploits
None indexed
Exploitation data as of Sep 22, 2026 · OSV.dev, NVD, FIRST.org (EPSS)

Exploitation Status

No confirmed exploitation observed yet

  • CISA’s own triage has not observed active exploitation or public proof-of-concept code for this CVE as of its last assessment.

Exploitation and automatability from CISA’s SSVC triage for CVE-2026-27695.

EPSS Exploitation Probability

via FIRST.org ↗
0.2%probability of exploitation in next 30 days
Lower Risk0.00%
Lower risk than most CVEs14th percentile — riskier than 14% of all scored CVEsHighest risk

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

CVE-2026-27695 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 378,567 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
🐍zae-limiter

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

Summary

All rate limit buckets for a single entity share the same DynamoDB partition key (namespace/ENTITY#{id}). A high-traffic entity can exceed DynamoDB's per-partition throughput limits (~1,000 WCU/sec), causing throttling that degrades service for that entity — and potentially co-located entities in the same partition.

Details

Each acquire() call performs a TransactWriteItems (or UpdateItem in speculative mode) against items sharing the same partition key. For cascade entities, this doubles to 2-4 writes per request (child + parent). At sustained rates above ~500 req/sec for a single entity, DynamoDB's adaptive capacity may not redistribute fast enough, causing ProvisionedThroughputExceededException.

The library has no built-in mitigation:

  • No partition key sharding/salting
  • No write coalescing or batching
  • No client-side admission control before hitting DynamoDB
  • RateLimiterUnavailable is raised but the caller has already been delayed

Impact

  • Availability: High-traffic entities experience elevated latency and rejected requests beyond what their rate limits specify
  • Fairness: Other entities sharing the same DynamoDB partition may experience collateral throttling
  • Multi-tenant risk: In a shared LLM proxy scenario, one tenant's burst traffic could degrade service for others

Reproduction

  1. Create an entity with high rate limits (e.g., 100,000 rpm)
  2. Send sustained traffic at 1,000+ req/sec to a single entity
  3. Observe DynamoDB ThrottledRequests CloudWatch metric increasing
  4. Observe acquire() latency spikes and RateLimiterUnavailable exceptions

Remediation Design: Pre-Shard Buckets

  • Move buckets to PK={ns}/BUCKET#{entity}#{resource}#{shard}, SK=#STATE — one partition per (entity, resource, shard)
  • Auto-inject wcu:1000 reserved limit on every bucket — tracks DynamoDB partition write pressure in-band (name may change during implementation)
  • Shard doubling (1→2→4→8) triggered by client on wcu exhaustion or proactively by aggregator
  • Shard 0 at suffix #0 is source of truth for shard_count. Aggregator propagates to other shards
  • Original limits stored on bucket, effective limits derived: original / shard_count. Infrastructure limits (wcu) not divided
  • Shard selection: random/round-robin. On application limit exhaustion, retry on another shard (max 2 retries)
  • Lazy shard creation on first access
  • Bucket discovery via GSI3 (KEYS_ONLY) + BatchGetItem. GSI2 for resource aggregation unchanged
  • Cascade: parent unaware, protected by own wcu
  • Aggregator: parse new PK format, key by shard_id, effective limits for refill, filter wcu from snapshots
  • Clean break migration: schema version bump, old buckets ignored, new buckets created on first access
  • $0.625/M preserved on hot path

Affected Packages

1 total 1 fixed
EcosystemPackageVulnerable rangeFix
🐍PyPIzae-limiterall versions0.10.1pip install --upgrade 'zae-limiter==0.10.1'

Detection & mitigation playbook

Open-source dependency
  1. Detect

    Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for zae-limiter, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.

  2. Fix

    Update zae-limiter to 0.10.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms CVE-2026-27695 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 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like CVE-2026-27695 can be triaged on real exposure rather than presence alone.

Tailored to CVE-2026-27695. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.

Frequently Asked Questions

## Summary All rate limit buckets for a single entity share the same DynamoDB partition key (`namespace/ENTITY#{id}`). A high-traffic entity can exceed DynamoDB's per-partition throughput limits (~1,000 WCU/sec), causing throttling that degrades service for that entity — and potentially co-located entities in the same partition. ## Details Each `acquire()` call performs a `TransactWriteItems` (or `UpdateItem` in speculative mode) against items sharing the same partition key. For cascade entities, this doubles to 2-4 writes per request (child + parent). At sustained rates above ~500 req/sec
O3 Security · Impact-Aware SCA

Is CVE-2026-27695 in your dependencies?

O3 Security finds CVE-2026-27695 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.

CVE-2026-27695: zae-limiter (Medium 4.3) | O3 Security