Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ArabelaTso/Skills-4-SE --skill taint-instrumentation-assistantgit clone --depth 1 https://github.com/ArabelaTso/Skills-4-SEWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/arabelatso/skills-4-se/taint-instrumentation-assistant)<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/taint-instrumentation-assistant"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/taint-instrumentation-assistant/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/arabelatso/skills-4-se/taint-instrumentation-assistant"><img src="https://agentmods.dev/badge/skills/arabelatso/skills-4-se/taint-instrumentation-assistant.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00117 | $0.02868 |
| Opus 5 | $0.00059 | $0.01434 |
| Sonnet 5 | $0.00023 | $0.00574 |
| Haiku 4.5 | $0.00012 | $0.00287 |
Grade A, and why
taint-instrumentation-assistant scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
os.system(f"cat {filename}") How it starts
The opening of the file, as written. The whole thing — 398 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Taint Instrumentation Assistant
Instrument code to track untrusted and sensitive data flow for security vulnerability detection.
Workflow
Follow these steps to add taint tracking instrumentation:
1. Identify Taint Sources and Sinks
Define what data to track and where violations occur:
Taint sources (untrusted/sensitive data origins):
- User input (HTTP parameters, form data, command-line args)
- File reads (configuration files, user uploads)
- Database queries (user-provided data)
- Network input (API responses, socket data)
- Environment variables
Taint sinks (dangerous operations):
- SQL queries (SQL injection risk)
- System commands (command injection risk)
- HTML output (XSS risk)
- File operations (path traversal risk)
- Eval/exec statements (code injection risk)
- Network output (data leak risk)
2. Instrument Taint Sources
Mark data from untrusted sources as tainted:
# Mark user input as tainted
def mark_tainted(value, source):
"""Mark a value as tainted from a specific source"""
if hasattr(value, '__taint__'):
value.__taint__ = source
return value
# Example: HTTP parameter
user_input = request.GET['username']
user_input = mark_tainted(user_input, source="HTTP_PARAM")
3. Propagate Taint Through Operations
Track taint as data flows through the program:
# Taint propagation for string operations
def tainted_concat(str1, str2):
result = str1 + str2
# If either input is tainted, result is tainted
if hasattr(str1, '__taint__') or hasattr(str2, '__taint__'):
result.__taint__ = getattr(str1, '__taint__', None) or getattr(str2, '__taint__', None)
return result
4. Check Taint at Sinks
Detect when tainted data reaches dangerous operations:
# Check for tainted data at SQL sink
def execute_query(query):
if hasattr(query, '__taint__'):
print(f"TAINT VIOLATION: Tainted data from {query.__taint__} used in SQL query")
print(f"Query: {query}")
# Optionally: raise exception or log for analysis
# Execute query...
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 398 lines · 117 tokens per session scan A c103790c6459
taint-instrumentation-assistant is a skill published in the GitHub repository ArabelaTso/Skills-4-SE (252 stars, last pushed 22d ago), licensed Apache-2.0. It adds 117 tokens to every session and 2,868 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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