Authorization Bypass Detection
Tencent/AI-Infra-Guard
Probes an AI agent through dialogue for cross-user data access, privilege escalation and login bypass, and reports confirmed findings as structured vulnerability entries.
Agent skill
Implementing Network Deception With Honeypots
Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.
Install Implementing Network Deception With Honeypots
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypots --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .claude/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .claude/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypotsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypots --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .agents/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .agents/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypots --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .cursor/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .cursor/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/implementing-network-deception-with-honeypots--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypots --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .gemini/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .gemini/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypotsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .github/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .github/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills implementing-network-deception-with-honeypots --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/implementing-network-deception-with-honeypots .opencode/skills/implementing-network-deception-with-honeypots && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "implementing-network-deception-with-honeypots" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/implementing-network-deception-with-honeypots into .opencode/skills/implementing-network-deception-with-honeypots/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "implementing-network-deception-with-honeypots", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
implementing-network-deception-with-honeypots- GitHub stars
- 34k
- Token cost
- ~762 tokens
- SKILL.md length
- 259 words
- Files
- 4 (incl. scripts, references)
- Skills in repo
- 644
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.
- Works in 7 steps: Plan Deployment: Select honeypot types… → Install Honeypot: Deploy OpenCanary,… → Configure Services: Enable emulated… → …
- Tasks that involve Red teaming and adversary simulation
- SKILL.md covers When to Use, Prerequisites, Workflow and Key Concepts, plus 2 more sections
- Runs Python scripts from its folder
What it does
Implementing Network Deception With Honeypots is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.
Its SKILL.md is about 760 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security, covering Red teaming and adversary simulation. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Red teaming and adversary simulation
Example prompts
- “/implementing-network-deception-with-honeypots”
Requirements
- Python 3
- Docker
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Plan Deployment: Select honeypot types and network placement strategy.
- Install Honeypot: Deploy OpenCanary, Cowrie, or T-Pot on dedicated host.
- Configure Services: Enable emulated services (SSH, HTTP, SMB, FTP, RDP).
- Set Up Alerting: Configure log forwarding to SIEM and alert channels.
- Deploy Canary Tokens: Place credential files, shares, and DNS entries.
- Monitor Interactions: Analyze honeypot logs for attacker activity.
- Tune and Maintain: Update configurations based on detection results.
What it can do on your machine
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Implementing Network Deception With Honeypots loads about 762 tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 49 tokens; SKILL.md has 259 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 259 words, ~762 tokens.
Download SKILL.mdSave it as
.claude/skills/implementing-network-deception-with-honeypots/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- implementing-network-deception-with-honeypots
- description
- Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.
- domain
- cybersecurity
- subdomain
- deception-technology
- tags
- deception, honeypot, opencanary, cowrie, t-pot, detection, lateral-movement, network-security
- version
- 1.0
- author
- mahipal
- license
- Apache-2.0
- nist_csf
- DE.CM-01, DE.AE-06, PR.IR-01
- mitre_attack
- T1078, T1190, T1059, T1021, T1550
Implementing Network Deception with Honeypots
When to Use
- When deploying deception technology to detect lateral movement
- To create early warning indicators for network intrusion
- During security architecture design to add detection depth
- When monitoring for unauthorized internal scanning or credential theft
- To gather threat intelligence on attacker techniques and tools
Prerequisites
- Linux server or VM for honeypot deployment (Ubuntu 22.04+ recommended)
- Python 3.8+ with pip for OpenCanary installation
- Docker for T-Pot or containerized deployment
- Network segment with appropriate VLAN configuration
- SIEM integration for alert forwarding (syslog, webhook, or file-based)
- Firewall rules allowing inbound connections to honeypot services
Workflow
- Plan Deployment: Select honeypot types and network placement strategy.
- Install Honeypot: Deploy OpenCanary, Cowrie, or T-Pot on dedicated host.
- Configure Services: Enable emulated services (SSH, HTTP, SMB, FTP, RDP).
- Set Up Alerting: Configure log forwarding to SIEM and alert channels.
- Deploy Canary Tokens: Place credential files, shares, and DNS entries.
- Monitor Interactions: Analyze honeypot logs for attacker activity.
- Tune and Maintain: Update configurations based on detection results.
Key Concepts
| Concept | Description |
|---|---|
| OpenCanary | Lightweight Python honeypot with modular service emulation |
| Cowrie | Medium-interaction SSH/Telnet honeypot capturing commands |
| T-Pot | Multi-honeypot platform with ELK stack visualization |
| Canary Token | Tripwire credential or file that alerts when accessed |
| Low-Interaction | Emulates services at protocol level without full OS |
| High-Interaction | Full OS honeypot capturing complete attacker sessions |
Tools & Systems
| Tool | Purpose |
|---|---|
| OpenCanary | Modular honeypot daemon with service emulation |
| Cowrie | SSH/Telnet honeypot with session recording |
| T-Pot | All-in-one multi-honeypot platform |
| Dionaea | Malware-capturing honeypot for exploit detection |
| Splunk/Elastic | SIEM for honeypot alert aggregation |
Output Format
Alert: HONEYPOT-[SERVICE]-[DATE]-[SEQ]
Honeypot: [Hostname/IP]
Service: [SSH/HTTP/SMB/FTP/RDP]
Source IP: [Attacker IP]
Interaction: [Login attempt/Port scan/File access]
Credentials Used: [Username:Password if applicable]
Commands Executed: [For SSH honeypots]
Risk Level: [Critical/High/Medium/Low]© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 3 other files (scripts, references) in skills/implementing-network-deception-with-honeypots of mukul975/Anthropic-Cybersecurity-Skills.
- SKILL.md
- LICENSE
- references/api-reference.md
- scripts/agent.py
Open the folder on GitHubat commit 54a7988
Compare with similar skills
Implementing Network Deception With Honeypots next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Implementing Network Deception With Honeypots this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~762 | Automated safety check: Pass | Apache-2.0 | |
| Authorization Bypass DetectionTencent/AI-Infra-Guard | 6.8k | — | ~753 | Automated safety check: Pass | Apache-2.0 | |
| Run Assert Evalresponsibleai/ASSERT | 330 | — | ~11k | Automated safety check: Notes | MIT | |
| Osint Methodologyelementalsouls/Claude-OSINT | 2.8k | — | ~8.7k | Automated safety check: Notes | MIT | |
| Lfd Designelvisun/loss-function-development | 176 | — | ~2.9k | Automated safety check: Notes | MIT | |
| Acl AbuseADScanPro/Claude-AD | 211 | — | ~2.6k | Automated safety check: Pass | MIT |
Similar skills
Run Assert Eval
responsibleai/ASSERT
Run an ASSERT evaluation against a described risk. An agent skill from responsibleai/ASSERT.
Osint Methodology
elementalsouls/Claude-OSINT
Comprehensive OSINT methodology for external red-team operations and authorized attack-surface assessments.
Lfd Design
elvisun/loss-function-development
Design a loss function and harness for a long-running /goal optimization run (loss-function development, LFD).
Acl Abuse
ADScanPro/Claude-AD
Abusing Active Directory object ACLs (DACL/ownership) for privilege escalation and lateral movement (GenericAll, GenericWrite, WriteDACL, WriteOwner, AddMember, ForceChangePassword, and replication…
Web Exfiltration Detection
Tencent/AI-Infra-Guard
Probes whether an agent with web fetch and stored user memory can be tricked by a malicious page into leaking data through chained URL paths.
More from mukul975/Anthropic-Cybersecurity-Skills
All 644 skills in this repoCampaign Attribution Evidence Analysis
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
Go Malware Analysis in Ghidra
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
LNK and Jump List Forensics
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
Malware Persistence Analysis with Autoruns
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
NTFS MFT Deleted File Recovery
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
Network Covert Channel Analysis
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Related
Categories
Questions about Implementing Network Deception With Honeypots
What does Implementing Network Deception With Honeypots do?
Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance. Implementing Network Deception With Honeypots is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Deploy and manage network honeypots using OpenCanary, T-Pot, or Cowrie to detect unauthorized access, lateral movement, and attacker reconnaissance.
When should I use Implementing Network Deception With Honeypots?
Implementing Network Deception With Honeypots fits situations like: tasks that involve Red teaming and adversary simulation.
How do I install Implementing Network Deception With Honeypots in Claude Code?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a claude-code`. Or copy the skill folder (skills/implementing-network-deception-with-honeypots in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/implementing-network-deception-with-honeypots in your project. Claude Code loads it when a task matches its description.
How do I install Implementing Network Deception With Honeypots in Codex?
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a codex`. Or copy the skill folder (skills/implementing-network-deception-with-honeypots in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/implementing-network-deception-with-honeypots in your project. Codex loads it when a task matches its description.
Can I use Implementing Network Deception With Honeypots in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill implementing-network-deception-with-honeypots -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implementing-network-deception-with-honeypots, .gemini/skills/implementing-network-deception-with-honeypots, .github/skills/implementing-network-deception-with-honeypots and .opencode/skills/implementing-network-deception-with-honeypots in your project.
What does Implementing Network Deception With Honeypots need to run?
Going by SKILL.md and its folder, Implementing Network Deception With Honeypots needs Python for the scripts in its folder. Our summary lists: Python 3; Docker.
Does Implementing Network Deception With Honeypots access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Implementing Network Deception With Honeypots safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Implementing Network Deception With Honeypots use?
Implementing Network Deception With Honeypots is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Implementing Network Deception With Honeypots use?
About 762 tokens (SKILL.md is roughly 3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 725 tokens, read only when the agent opens those files.
What are the alternatives to Implementing Network Deception With Honeypots?
Skills that share tags, products or a category with Implementing Network Deception With Honeypots: Authorization Bypass Detection (Tencent/AI-Infra-Guard, 6.8k stars), Run Assert Eval (responsibleai/ASSERT, 330 stars), Osint Methodology (elementalsouls/Claude-OSINT, 2.8k stars) and Lfd Design (elvisun/loss-function-development, 176 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Implementing Network Deception With Honeypots?
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.