Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.
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 uphiago/recon-skills --skill tls-fingerprint-impersonationgit clone --depth 1 https://github.com/uphiago/recon-skillsWrote 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/uphiago/recon-skills/tls-fingerprint-impersonation)<a href="https://agentmods.dev/skills/uphiago/recon-skills/tls-fingerprint-impersonation"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/tls-fingerprint-impersonation/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/uphiago/recon-skills/tls-fingerprint-impersonation"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/tls-fingerprint-impersonation.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 | $0.00022 | $0.02293 |
| Opus 5 | $0.00011 | $0.01146 |
| Sonnet 5 | $0.00004 | $0.00459 |
| Haiku 4.5 | $0.00002 | $0.00229 |
Grade A, and why
tls-fingerprint-impersonation 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 12d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
compatibility: Requires curl, httpx, python3 How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
TLS Fingerprint Impersonation
Spoof TLS ClientHello parameters — cipher suites, key exchange groups, signature algorithms, and extension order — to match real browsers at the JA3/JA4 fingerprint level. Uses patched rustls to rebuild the TLS layer with browser-identical configurations. Bypasses TLS fingerprinting detection (Cloudflare, Akamai, F5) that flags non-browser TLS stacks. Supports 20 browser profiles including Chrome 100-142, Firefox 128-144, Safari iOS 18, and OkHttp 3-5 (Android).
When to Use
- Target returns 403/blocked on curl/httpx even with correct User-Agent headers.
- Cloudflare or Akamai is fingerprinting TLS ClientHello (JA3/JA4 mismatch with browser).
- API probing requires mobile-app impersonation (OkHttp fingerprint for Android).
- Need high-throughput HTTP requests that pass TLS fingerprint checks without running a full browser.
- Target shows different behavior based on TLS fingerprint (mobile vs desktop endpoints).
Prerequisites
terminalwith python3.- Python:
pip install impit(wraps the Rust library via PyO3). - Or Node.js:
npm install impit(native binding). - Or Rust:
impitcrate with patched dependencies in Cargo.toml.
Quick Detection
# Check if a target blocks non-browser TLS
curl --max-time 30 --connect-timeout 10 -sk https://target.com | head -1
# If 403, test with browser impersonation:
python3 -c "
from impit import Impit
impit = Impit.builder().with_fingerprint('chrome142').build()
r = impit.get('https://target.com').text
print(r[:200])
"
Procedure
Phase 1 — Browser Profile Selection
Choose the right fingerprint for your target:
| Profile | Use case | Key differentiator |
|---|---|---|
chrome142 |
Modern desktop | Latest Chrome, post-quantum KEX (X25519MLKEM768), GREASE |
chrome100 |
Legacy systems | Older cipher suites, no GREASE in key exchange |
firefox144 |
Firefox desktop | Different pseudo-header order, FFDHE groups, SHA-1 signatures |
safari_ios18 |
iOS mobile | 3DES ciphers, duplicate signature algorithm, no session tickets |
okhttp4 |
Android apps | BoringSSL profile, no GREASE, no ECH, simpler cipher suites |
chrome124 |
Common default | Good balance of modern compatibility and detection pass rate |
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.
- 12d ago First seen · 238 lines · 22 tokens per session scan A 7f8496bcded9
tls-fingerprint-impersonation is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 11d ago), licensed MIT. It adds 22 tokens to every session and 2,293 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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