Who it is for
Long-term memory for AI Agents
pyproject.toml:8
Scanned repository says: Long-term memory for AI Agents
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Critical finding · details withheld for 30 days
Inspect the findingsRuntime safety, real-world agent capability, fitness for your use case or independent certification.
Structured, cited information from the scanned archive. Repository-authored claims are labeled and never treated as verified capabilities.
Long-term memory for AI Agents
pyproject.toml:8No explicit capability or integration was extracted; that does not mean none exists.
Manifest declares Python >=3.10,<4.0 as a requirement.
pyproject.toml:15Declares a dependency on qdrant-client.
pyproject.toml:17Declares a dependency on pydantic.
pyproject.toml:18Declares a dependency on openai.
pyproject.toml:19Declares a dependency on httpx.
pyproject.toml:20Declares a dependency on posthog.
pyproject.toml:21Declares a dependency on pytz.
pyproject.toml:22A license or copying file is present; its terms have not been reviewed.
LICENSE:1These are references in selected source files, not proof that a feature works at runtime.
Read from commit b7ad69a at Oct 12, 2026, 5:15 AM UTC. Source links open that exact commit. Repository statements are unreviewed and do not affect the score.
Critical details are withheld publicly for the first 30 days after a scan. A matched pattern is a lead for investigation, not a confirmed vulnerability.
Dependencies: 315 exact runtime versions from poetry.lock checked against OSV.dev on Oct 12, 2026; 36 with known advisories. Reachability is not checked.
Details are withheld from public view for 30 days after the scan. The owner can see them in full.
Review the private assessment and address the finding.
Details are withheld from public view for 30 days after the scan. The owner can see them in full.
Review the private assessment and address the finding.
Details are withheld from public view for 30 days after the scan. The owner can see them in full.
Review the private assessment and address the finding.
A SQL statement is assembled by inserting values into the query text. If any of those values comes from a user or from model output, as in text-to-SQL agents, it can rewrite the query.
Pass values as bound parameters and allow-list identifiers such as table and column names.
A SQL statement is assembled by inserting values into the query text. If any of those values comes from a user or from model output, as in text-to-SQL agents, it can rewrite the query.
Pass values as bound parameters and allow-list identifiers such as table and column names.
A model request does not set a maximum output length. One unusual input can produce a very long, expensive response.
Set max_tokens or the provider's equivalent on each model call.
A model request does not set a maximum output length. One unusual input can produce a very long, expensive response.
Set max_tokens or the provider's equivalent on each model call.
Model output is used without being checked against a schema. Unexpected or malformed output can break later steps or be trusted when it should not be.
Validate model output with Zod, JSON Schema, Pydantic or provider structured output.
Model output is used without being checked against a schema. Unexpected or malformed output can break later steps or be trusted when it should not be.
Validate model output with Zod, JSON Schema, Pydantic or provider structured output.
A model call has no visible fallback. If the provider fails or is rate limited, the whole agent fails with it.
Configure a secondary model or explicit fallback path for provider failures.
Metal Mantra could not confirm that the owner controls the stated domain. The domain may belong to someone else.
Verify the domain using the Metal Mantra DNS TXT challenge.
anyio 4.9.0 (PyPI) has known advisories: GHSA-5p39-cfhj-2xmp, GHSA-82r6-8w77-94w6, PYSEC-2026-4024, PYSEC-2026-4025 (highest severity critical). AnyIO: TLSStream IDNA 2003 host name encoding enables potential TLS certificate spoofing
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
chromadb 1.5.9 (PyPI) has known advisories: GHSA-2wm9-hf6c-p5cr, GHSA-36p7-vc44-83pf, GHSA-f4j7-r4q5-qw2c, GHSA-xph7-9rjv-w5fr, PYSEC-2026-311 (highest severity critical). ChromaDB has a code injection vulnerability
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
azure-core 1.35.0 (PyPI) has known advisories: GHSA-jm66-cg57-jjv5, PYSEC-2026-1208 (highest severity high). Azure Core is vulnerable to deserialization of untrusted data
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
The code returns the model's raw text. Output that was never parsed or validated can pass mistakes straight to users or other systems.
Parse and validate the result before returning it.
The code returns the model's raw text. Output that was never parsed or validated can pass mistakes straight to users or other systems.
Parse and validate the result before returning it.
No privacy policy link was found on the stated homepage. Buyers cannot see how the vendor handles their data.
Expose a clear Privacy Policy link on the official homepage.
No terms link was found on the stated homepage. Buyers cannot see the conditions that apply to using the service.
Expose a clear Terms link on the official homepage.
aiohttp 3.13.5 (PyPI) has known advisories: GHSA-2fqr-mr3j-6wp8, GHSA-4fvr-rgm6-gqmc, GHSA-4m7w-qmgq-4wj5, GHSA-63hw-fmq6-xxg2, GHSA-9x8q-7h8h-wcw9 (highest severity moderate). aiohttp: HTTP/1 Pipelined Requests Queue Without Limit
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
authlib 1.6.10 (PyPI) has known advisories: GHSA-jj8c-mmj3-mmgv, GHSA-r95x-qfjj-fjj2, PYSEC-2026-188, PYSEC-2026-25 (highest severity moderate). Authlib: Cross-site request forging when using cache
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
filelock 3.18.0 (PyPI) has known advisories: GHSA-qmgc-5h2g-mvrw, GHSA-w853-jp5j-5j7f, PYSEC-2026-1374, PYSEC-2026-1375 (highest severity moderate). filelock Time-of-Check-Time-of-Use (TOCTOU) Symlink Vulnerability in SoftFileLock
Upgrade to a fixed version listed in the advisory and regenerate the lockfile.
Each pillar starts at 100. Rule deductions reduce its score; weights determine the overall contribution.
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Share the full report so its scope and limits travel with the score.