GHSA-76rv-2r9v-c5m6 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
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 GHSA-76rv-2r9v-c5m6.
EPSS Exploitation Probability
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-76rv-2r9v-c5m6 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
zae-limiterReal-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
RateLimiterUnavailableis 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
- Create an entity with high rate limits (e.g., 100,000 rpm)
- Send sustained traffic at 1,000+ req/sec to a single entity
- Observe DynamoDB
ThrottledRequestsCloudWatch metric increasing - Observe
acquire()latency spikes andRateLimiterUnavailableexceptions
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:1000reserved 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
wcuexhaustion or proactively by aggregator - Shard 0 at suffix
#0is source of truth forshard_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
wcufrom 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
| Ecosystem | Package | Vulnerable range | Fix |
|---|---|---|---|
| 🐍PyPI | zae-limiter | all versions | 0.10.1pip install --upgrade 'zae-limiter==0.10.1' |
Detection & mitigation playbook
Open-source dependencyDetect
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.
Fix
Update zae-limiter to 0.10.1 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-76rv-2r9v-c5m6 is resolved across your whole dependency graph.
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.
How O3 protects you
O3 Security's impact-aware SCA analyses which vulnerable code paths your application actually calls, so a match like GHSA-76rv-2r9v-c5m6 can be triaged on real exposure rather than presence alone.
Tailored to GHSA-76rv-2r9v-c5m6. Runtime protection reduces exposure until a permanent patch is applied and verified — it complements patching, it doesn't replace it.
Frequently Asked Questions
Is GHSA-76rv-2r9v-c5m6 in your dependencies?
O3 Security finds GHSA-76rv-2r9v-c5m6 across PyPI dependencies, including transitive ones, and its impact-aware SCA ranks findings by whether your code actually calls the vulnerable path.