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anxolerd/dvpwa ↗ · a1d8f89 · Aug 21, 2026, 11:10 PM
We found hard evidence. 4 things need your attention now.We found real evidence of problems. 4 things need your attention now.4 issues need attention now.
Free scan · deterministic evidence onlyFree scan · found by automatic checks onlyFree scan · deterministic evidence only
These are facts from deterministic scanners, not opinion — 4 high/critical dependency vulnerabilities. The full picture — architecture, AI-generated-code risk, privacy, and 11 more dimensions — needs Audit.
These are facts found by automatic checks, not opinions — 4 serious security bugs in the ready-made packages your project uses. The full picture — how your code is built, AI-generated-code risk, privacy, and 11 more areas — needs Audit.
4 critical dependency vulnerabilities found. 11 more dimensions need Audit for the full picture.
33 of 58 files scanned (56%). Nothing was cut short by a limit — the rest is mostly images, generated output, and other non-source content this audit doesn't read.
What this meansWhat this means for youWhat this means
Two scanners read 33 of 58 files: one for committed credentials, one for known vulnerabilities in your dependencies. They found 0 committed credentials on production paths and 4 high or critical vulnerabilities in runtime dependencies. These two checks cover a narrow slice of what decides whether software is ready to ship. All 14 dimensions — architecture, privacy, reliability, AI-generated-code risk and the rest — are unexamined here. Deep AI is the tier that issues a verdict. This scan does not.
Read it:
Packages you ship with known vulnerabilities
cvePyPI pyyaml2 in 1 version
3.13 — GHSA-8q59-q68h-6hv4, GHSA-rprw-h62v-c2w7
Improper Input Validation in PyYAML — CRITICAL
PyYAML insecurely deserializes YAML strings leading to arbitrary code execution — CRITICAL
cvePyPI idna@2.8PYSEC-2024-60
A vulnerability was identified in the kjd/idna library, specifically within the `idna.encode()` function, affecting version 3.6. The issue arises from the function's handling of crafted input strings, — CVSS CVSS:3.1/AV:N/AC:L/PR:N/UI:N/S:U/C:N/I:N/A:H
cvePyPI jinja2@2.10GHSA-462w-v97r-4m45
Jinja2 sandbox escape via string formatting — HIGH
Worth knowing, not blocking
low cvePyPI aiohttp3 in 1 version
3.5.3 — GHSA-2fqr-mr3j-6wp8, GHSA-2vrm-gr82-f7m5, GHSA-3wq7-rqq7-wx6j
aiohttp: Host-Only Cookies Become Domain Cookies After CookieJar Persistence — LOW
AIOHTTP has CRLF injection through multipart part content type header construction — LOW
AIOHTTP has late size enforcement for non-file multipart fields causes memory DoS — LOW
moderate cvePyPI idna2 in 1 version
2.8 — GHSA-65pc-fj4g-8rjx, GHSA-jjg7-2v4v-x38h
Internationalized Domain Names in Applications (IDNA): Specially crafted inputs to idna.encode() can bypass CVE-2024-3651 fix — MODERATE
Internationalized Domain Names in Applications (IDNA) vulnerable to denial of service from specially crafted inputs to idna.encode — MODERATE
moderate cvePyPI jinja22 in 1 version
2.10 — GHSA-cpwx-vrp4-4pq7, GHSA-g3rq-g295-4j3m
Jinja2 vulnerable to sandbox breakout through attr filter selecting format method — MODERATE
Regular Expression Denial of Service (ReDoS) in Jinja2 — MODERATE
advisory cvePyPI pyyaml@3.13PYSEC-2018-49
In PyYAML before 5.1, the yaml.load() API could execute arbitrary code if used with untrusted data. The load() function has been deprecated in version 5.1 and the 'UnsafeLoader' has been introduced fo — UNKNOWN
AI audit for anxolerd/dvpwa · all 14 dimensions · usually within 15 minutes*AI check for anxolerd/dvpwa · all 14 areas · usually within 15 minutes*AI audit · anxolerd/dvpwa · 14 dimensions · usually within 15 minutes*
14 things we haven't looked at yet14 things we haven't checked yet14 things unaudited
Security logic, privacy, reliability, AI-generated-code risk and 10 more — unaudited, not clean.Security logic, privacy, reliability, AI-generated-code risk and 10 more — not checked yet, which is different from safe.Security, privacy, reliability, AI-generated-code risk, 10 more: unaudited, not clean.
The free scan reasons across none of these. Absence of findings is reported as unaudited, not safe. Opus 4.8 reads the code semantically and scores every one — with evidence, business impact, and a fix per finding.
The free scan doesn't look at any of these. If nothing is flagged here, that means it wasn't checked — not that it's safe. Opus 4.8 (the AI model behind the audit) reads and understands your code and scores every one of these — with evidence, the real-world impact, and a fix for each finding.
The free scan doesn't reason across these — unaudited, not safe. Opus 4.8 scores each, with evidence, impact, and a fix.
SecurityPriority: Core
Privacy & CompliancePriority: Core
Reliability & ResiliencePriority: Core
Code Quality & ArchitecturePriority: Important
AI / Vibe Coding RiskPriority: Important
Performance & ScalabilityPriority: Important
Infrastructure & DevOpsPriority: Important
Data LayerPriority: Important
Business & Product RiskPriority: Supporting
Developer ExperiencePriority: Supporting
Accessibility & UXPriority: Supporting
ObservabilityPriority: Supporting
Maintainability ForecastPriority: Specialized
IP & Novelty ExposurePriority: Specialized
Modules run (2)
Hardcoded Secret ScanDependency Vulnerability Scan
Scanned 33 of 58 files · anxolerd/dvpwa
Dependency manifests: 1 Python manifest read.
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