How severe is GHSA-j659-8xh6-5pq5?

No CVSS score has been assigned to GHSA-j659-8xh6-5pq5 yet. Review the advisory details and affected package list to assess your exposure.

Which packages are affected by GHSA-j659-8xh6-5pq5?

GHSA-j659-8xh6-5pq5 affects the following packages: atomic-agents-stack (PyPI). Ecosystems affected: PyPI.

How do I fix GHSA-j659-8xh6-5pq5?

Update atomic-agents-stack to 1.1.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-j659-8xh6-5pq5 is resolved across your whole dependency graph.

How do I detect GHSA-j659-8xh6-5pq5 in my PyPI dependencies?

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

How do I mitigate GHSA-j659-8xh6-5pq5 if there is no patch (or I can't update yet)?

Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Is GHSA-j659-8xh6-5pq5 actively exploited in the wild?

No public exploit code has been indexed for GHSA-j659-8xh6-5pq5 yet. This does not mean the vulnerability cannot be exploited — absence of public exploits does not imply safety. Apply the recommended fix and use O3 Security to monitor your exposure.

What is the EPSS score for GHSA-j659-8xh6-5pq5?

GHSA-j659-8xh6-5pq5 has an EPSS (Exploit Prediction Scoring System) score of 0.5%, placing it in the 39th percentile of all CVEs. EPSS is maintained by FIRST.org and estimates the probability that a vulnerability will be exploited in the wild within the next 30 days. This score indicates relatively lower exploitation probability, though the CVSS severity should still guide your patching priority.

What type of vulnerability is GHSA-j659-8xh6-5pq5?

GHSA-j659-8xh6-5pq5 is classified as CWE-770 (CWE-770). This weakness type describe the underlying flaw category, which helps determine the potential impact and the right class of mitigation.

When was GHSA-j659-8xh6-5pq5 published, and has it been updated?

GHSA-j659-8xh6-5pq5 was published on August 17, 2026 and was last updated on September 16, 2026. Advisory data evolves as severity scores, affected ranges, and exploit intelligence are revised — always check the latest version of the advisory before acting.

🐍 PyPI

Not in CISA KEV

GHSA-j659-8xh6-5pq5 — atomic-agents-stack

GHSA-j659-8xh6-5pq5 is a CWE-770 vulnerability in atomic-agents-stack. A fix is available for atomic-agents-stack — see the affected versions and patch details below.

atomic-agents-stack: Parallel helper/delegate batch reserves $0 for models absent from the pricing table, bypassing the cost-cap fan-out guard

Also known asCVE-2026-91987

Published

Aug 17, 2026

Updated

Sep 16, 2026

Affected

1 pkg

Patched

1 / 1

Exploits

None indexed

Exploitation data as of Sep 30, 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 GHSA-j659-8xh6-5pq5.

EPSS Exploitation Probability

via FIRST.org ↗

0.5%probability of exploitation in next 30 days

Lower Risk0.00%

Lower risk than most CVEs39th percentile — riskier than 39% of all scored CVEsHighest risk

Probability of exploitation in the next 30 days, from FIRST.org EPSS.

Real-World Exposure

1 pkg affected

🐍atomic-agents-stack

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

_estimate_batch_cost (atomic_agents/agent.py) looks up the per-model output price with PRICING.get(model, {}), returning 0.0 for any model not in the hardcoded pricing table. _check_batch_reservation then early-returns when the reservation is <= 0, skipping the batch reservation entirely. That reservation is the only defense against the documented fan-out race where every parallel helper/delegate reads the identical pre-batch on-disk cost total and each passes its individual check even though the collective spend overruns the configured cap.

Impact: an operator running any model not in the pricing table (self-hosted/Ollama/vLLM, a new provider SKU) with cost_guardrails + daily_cap_usd set believes the cap protects them, but a single parallel batch can blow past the cap. The parallel-helper model argument can also be steered to an unknown id. The sibling dream._estimate_dream_cost does this correctly (PRICING.get(model, _fallback_pricing())), which makes this a clear defect.

Affected: agent.py (_estimate_batch_cost / _check_batch_reservation), all versions through 1.0.0.

Fix: use PRICING.get(model, _costs._fallback_pricing())['output'] (mirror dream/calc_cost). Add a conformance test asserting an unknown-model batch reserves > 0 and that an over-cap unknown-model batch raises CostGuardrailBlocked.

Affected Packages

1 total 1 fixed

Ecosystem	Package	Vulnerable range	Fix
🐍PyPI	`atomic-agents-stack`	all versions	1.1.0`pip install --upgrade 'atomic-agents-stack==1.1.0'`

Detection & mitigation playbook

Open-source dependency

Detect
Scan your dependency tree (package-lock.json, pnpm-lock.yaml, requirements.txt, go.sum, etc.) for atomic-agents-stack, including transitive dependencies — a direct dependency you never call can still pull in a vulnerable version.
Fix
Update atomic-agents-stack to 1.1.0 or later, then make sure no transitive (indirect) dependency still pins the vulnerable range — O3 confirms GHSA-j659-8xh6-5pq5 is resolved across your whole dependency graph.
Workarounds
Cap what an attacker can consume: apply request size, rate and timeout limits in front of the affected component, and run it with memory and CPU limits so exhaustion degrades one worker rather than the whole service.

Frequently Asked Questions

`_estimate_batch_cost` (`atomic_agents/agent.py`) looks up the per-model output price with `PRICING.get(model, {})`, returning 0.0 for any model not in the hardcoded pricing table. `_check_batch_reservation` then early-returns when the reservation is <= 0, skipping the batch reservation entirely. That reservation is the only defense against the documented fan-out race where every parallel helper/delegate reads the identical pre-batch on-disk cost total and each passes its individual check even though the collective spend overruns the configured cap. **Impact:** an operator running any model n

O3 Security · Impact-Aware SCA

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