AgentGuard — The Python SAST That Actually Fixes Your Code (Now Powered by GLM-5.2)

difcn@126.com — Tue, 23 Jun 2026 08:48:52 +0000

I scanned 15 popular Python projects for security bugs. The oldest one had the worst issue.

TL;DR

463 findings. 120 critical. The worst offender wasn't some weekend hobby project — it was a library used by the Python Software Foundation. It had eval() in production code. I fixed it.

I ran AgentGuard (65 rules + GLM-5.2 verification) against 15 well-known Python projects. Here's what I found — and what I fixed.

The Setup

$ agentguard scan ./project --tier pro --format json

AgentGuard is an open-source scanner with a twist: GLM-5.2 reviews every finding to filter false positives, then auto-generates fixes. Think Bandit + AI review + auto-fix in one command. GitHub | pip install agentguardp

The Results

15 projects, 1K to 30K lines of Python each:

Project	Stars	Findings	Critical	High	Top Issue
paramiko	3.5K	185	52	4	Hardcoded keys, path traversal
httpx	13K	55	32	4	Hardcoded secrets, pickle
click	16K	41	0	5	while-True loops, PY050
flask	68K	36	3	12	eval/exec (by design), DEBUG=True
tqdm	28K	30	0	2	SSRF in examples
python-jose	1.7K	27	20	0	Private keys in test fixtures
rich	50K	25	0	0	while-True, weak random
data-diff	3K	25	2	22	MD5, SSRF
httpie	34K	14	0	6	SSRF, SSL verify=False
pydantic	20K	10	5	2	pickle, hardcoded secrets
requests-html	13K	7	5	0	eval() in production
arq	2K	5	0	0	assert statements
tweets_analyzer	3K	2	1	0	Hardcoded API keys (template)
wikipedia	3K	1	0	1	SSRF
m2cgen	3K	0	0	0	Clean!

Total: 463 findings / 120 critical / 58 high

The Best Find: eval() in a PSF Library

requests-html (13K Stars, maintained by the Python Software Foundation) had this in its core:

# requests_html.py:570
def __convert(cookiejar, key):
    try:
        v = eval("cookiejar." + key)  # <-- INJECTION RISK

AgentGuard's GLM-5.2 cloud fix suggested replacing it with getattr():

# After fix
v = getattr(cookiejar, key, None)

I submitted a PR: psf/requests-html#610

Top 5 Most Common Issues

assert for security checks (107) — removed in python -O, check silently disappears
Path traversal (82) — user-controlled paths without validation
Hardcoded secrets (67) — API keys, passwords in source code
Unbounded loops (42) — while True: without timeout
Weak random (24) — random instead of secrets

Why GLM-5.2 Matters

Model	F1 Score (Vuln Detection)	Cost per Finding
Claude Code	32-37%	~$1.02
GLM-5.2	39%	$0.17

GLM-5.2 outperforms Claude Code in security detection at 1/6 the cost. AgentGuard is the first tool to productize this.

Source: Semgrep security evaluation (cybernexora.com, paddo.dev)

The Pipeline

$ agentguard pipeline ./vulnerable.py --mode dry-run

[1/4] Scanning... 6 findings
[2/4] GLM-5.2 verifying... 6 confirmed, 0 rejected
[3/4] Fixing... 4 auto-fixed, 2 need manual review
[4/4] Validating... No new issues introduced

Rules find suspects. GLM-5.2 confirms, fixes, and verifies.

Try It

pip install agentguardp
agentguard scan ./your-project
agentguard pipeline ./src --mode dry-run

14-day Pro trial included. GLM-5.2 cloud fix activates automatically.

GitHub: https://github.com/difcn2026/agentguardp
PyPI: https://pypi.org/project/agentguardp/
Website: https://agentguardp.com

Scanned and auto-fixed by AgentGuard + GLM-5.2.

DEV Community: difcn@126.com