HackSkills is an organized knowledge base of installable skills that gives AI agents practical security knowledge across areas such as web security, privilege escalation, reverse engineering, and digital forensics. It is intended for bug bounty work, penetration testing, CTF competitions, and authorized security research. The catalogue entries are the project's own master, category, and topic skills.
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 yaklang/hack-skills --skill clickjackinggit clone --depth 1 https://github.com/yaklang/hack-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/yaklang/hack-skills/clickjacking)<a href="https://agentmods.dev/skills/yaklang/hack-skills/clickjacking"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/clickjacking/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/yaklang/hack-skills/clickjacking"><img src="https://agentmods.dev/badge/skills/yaklang/hack-skills/clickjacking.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- 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 | $0.00047 | $0.01253 |
| Opus 5.5 | $0.00019 | $0.00501 |
| Sonnet 5.5 | $0.00009 | $0.00251 |
| Haiku 4.5 | $0.00005 | $0.00125 |
Grade A, and why
clickjacking scanned grade A with 0 findings 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 1mo 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
6 near-identical copies found in the catalogue:
- clickjacking — 100% identical, 0 lines differ
- clickjacking — 100% identical, 0 lines differ
- clickjacking — 100% identical, 0 lines differ
- clickjacking — 100% identical, 0 lines differ
- clickjacking — 100% identical, 0 lines differ
- clickjacking — 94% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SKILL: Clickjacking — Expert Attack Playbook
AI LOAD INSTRUCTION: Clickjacking (UI redress) techniques. Covers iframe transparency tricks, X-Frame-Options bypass, CSP frame-ancestors, multi-step clickjacking, drag-and-drop attacks, and chaining with other vulnerabilities. Often a "low severity" finding that becomes critical when targeting admin actions.
1. CORE CONCEPT
Clickjacking loads a target page in a transparent iframe overlaid on an attacker's page. The victim sees the attacker's UI but clicks on the invisible target page, performing unintended actions.
<style>
iframe { position: absolute; top: 0; left: 0; width: 100%; height: 100%; opacity: 0.0001; z-index: 2; }
.decoy { position: absolute; top: 200px; left: 100px; z-index: 1; }
</style>
<div class="decoy"><button>Click to win a prize!</button></div>
<iframe src="https://target.com/account/delete?confirm=yes"></iframe>
2. DETECTION — IS THE PAGE FRAMEABLE?
Check X-Frame-Options Header
X-Frame-Options: DENY → cannot be framed (secure)
X-Frame-Options: SAMEORIGIN → only same-origin framing (secure for cross-origin)
X-Frame-Options: ALLOW-FROM uri → deprecated, browser support inconsistent
(header absent) → frameable! (vulnerable)
Check CSP frame-ancestors
Content-Security-Policy: frame-ancestors 'none' → cannot be framed
Content-Security-Policy: frame-ancestors 'self' → same-origin only
Content-Security-Policy: frame-ancestors https://a.com → specific origin
(directive absent) → frameable
CSP frame-ancestors supersedes X-Frame-Options in modern browsers.
Quick PoC Test
<iframe src="https://target.com/sensitive-action" width="800" height="600"></iframe>
If the page loads in the iframe → frameable → potentially vulnerable.
JavaScript Frame Detection (from target page source)
// Common frame-busting code found in target pages:
if (top.location.hostname !== self.location.hostname) {
top.location.href = self.location.href;
}
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.
- 1mo ago First seen · 164 lines · 47 tokens per session scan A e8d576fea77e
clickjacking is a skill published in the GitHub repository yaklang/hack-skills (2,460 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 1,253 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
tika-eval-compare
Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
jetson-validate-image
Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.
atmos-validation
Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.