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5g 6g Telecom Attack Advanced

Community
brucesongs
5g-6g-telecom-attack-advanced

Advanced 5G/6G telecom attacks covering 5G Core (SBA) exploitation, IMSI catcher evolution (5G Stingray), SIP/Diameter protocol attacks, Open RAN vulnerabilities, network slicing abuse, and early 6G research vectors (THz comms, AI-native air interface).

Overview

Publisherbrucesongs
Repositorykali-claw
Skill name5g-6g-telecom-attack-advanced
Stars
70
Forks
18
Bundled files
9
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 9 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by brucesongs on GitHub. Read the source before you install it.

Installation

Install the 5g 6g Telecom Attack Advanced AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/brucesongs/kali-claw.git /tmp/kali-claw
mkdir -p .claude/skills
cp -r /tmp/kali-claw/skills/5g-6g-telecom-attack-advanced .claude/skills/5g-6g-telecom-attack-advanced
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 5g 6g Telecom Attack Advanced in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads 5g 6g Telecom Attack Advanced on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so 5g 6g Telecom Attack Advanced is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Skill: 5g-6g-telecom-attack-advanced

Summary

Advanced 5G/6G telecom attacks covering 5G Core (SBA) exploitation, IMSI catcher evolution (5G Stingray), SIP/Diameter protocol attacks, Open RAN vulnerabilities, network slicing abuse, and early 6G research vectors (THz comms, AI-native air interface).

Tools: garak, PyRIT, promptfoo, custom harnesses

Domain: telecom

MITRE: TA0001-Initial Access, T1557-Adversary-in-the-Middle

Description

Advanced 5G/6G telecom attacks covering 5G Core (SBA) exploitation, IMSI catcher evolution (5G Stingray), SIP/Diameter protocol attacks, Open RAN vulnerabilities, network slicing abuse, and early 6G research vectors (THz comms, AI-native air interface).

This skill covers the offensive side of telecom-advanced security, including reconnaissance, vulnerability discovery, exploitation, persistence, and reporting. Aligned with OWASP Top 10, MITRE ATT&CK, and industry-specific compliance frameworks.


Use Cases

  1. 5G Core (SBA) exploitation: Abuse NF (Network Function) APIs for unauthorized access.
  2. IMSI catcher evolution: 5G Stingray that forces fallback to 4G/3G for SUPI disclosure.
  3. SIP/Diameter attacks: Signaling attacks via Diameter/SIP protocols.
  4. Open RAN vulnerabilities: Exploit O-RAN fronthaul splits for RAN compromise.
  5. Network slicing abuse: Escape network slice isolation.
  6. 6G research: Early attack research on THz communications, AI-native air interface.

Core Tools

| srsRAN | Open-source 5G RAN + Core | srsran-enb / srsran-gnb | | Open5GS | Open-source 5G Core | open5gs-pgwd | | sipp | SIP/Diameter testing | sipp -sf scenario.xml | | WireShark | Protocol analysis | Decode 5G protocols | | Py Crate | Protocol testing | pycrate_diameter.py | | Scapy | Custom protocol crafting | send(IP()/UDP()/Diameter()) | | HackRF | SDR for radio attacks | hackrf_transfer |


Methodology

Attack Chain

[1] Reconnaissance         [2] Signaling Attack      [3] Core Exploitation
  - PLMN identification      - Diameter relay            - NF API abuse
  - UE attachment              - SIP REGISTER flood         - Cross-slice access
  - NF discovery              - SMS interception             - AUSF bypass
  - Slice mapping               |                            |
        |                        v                            v
        v             [2.5] Radio Attack       [4] Persistence
[1.5] IMSI catcher      - 5G Stingray             - Rogue NF
  - Force fallback        - IMSI disclosure          - Persistent slice
  - SUCI bypass           - TMSI tracking              |
  - SUPI extraction         |                          v
                            v            [5] Reporting
                          [4] Persistence   - Signaling audit
                          - Rogue base      - Slice compromise
                          - Persistent radio - Regulatory impact

Defense Perspective

Defense LayerMeasuresKey Points
SUCI ProtectionMandatory SUCI (Subscription Concealed Identifier) for privacy; strong ECIES encryption5G improves over 4G IMSI; deploy properly
NF API SecurityMutual TLS between NFs; OAuth2 for SBI; strict API allowlistSBA architecture exposes APIs; protect each
Diameter FirewallMessage filtering; STP signaling firewall; route validationDiameter is SS7 successor; protect accordingly
Slice IsolationPer-slice NF; per-slice QoS; per-slice security policySlice is tenant boundary; enforce isolation
Open RAN SecurityEncrypt fronthaul; authenticate O-RAN components; harden near-RT RICO-RAN introduces new attack surface; secure supply chain
Core Network Isolation5G Core in private network; only N6 (internet) interface exposedReduce attack surface; core not directly internet-facing

Practical Steps

See payloads.md for detailed payloads and test-cases.md for the complete test checklist.

1. Reconnaissance

Identify target infrastructure; fingerprint products; enumerate attack surface.

2. Vulnerability Discovery

Run automated scanners (garak, PyRIT); manual testing per OWASP Top 10.

3. Exploitation

Chain vulnerabilities for maximum impact; document PoC.

4. Persistence

Establish persistence via configuration changes, scheduled tasks, or backdoors.

5. Reporting

Map findings to MITRE ATT&CK, OWASP, regulatory frameworks; include concrete remediation.


Detection Methods

5G Core (SBA) Detection

  • SBI anomaly detection: Northbound API requests from unexpected Network Functions (NF); abnormal requester-respondent patterns.
  • Diameter/SIP signaling storms: Signaling rate exceeding baseline.
  • AUSF/UDM anomaly: Authentication vector requests for inactive IMSIs.

Radio Access Network (RAN) Indicators

  • IMSI Catcher signatures: Tracking Area Update (TAU) storms; cells with same PLMN but unusual TAC.
  • Rogue gNodeB: Cell ID not in operator database; tracking area code mismatch.

SIEM / Probe Detection

  • 5G probe: Active probes for traffic analysis; detect signaling storms.
  • Splunk SPL (telecom probe): index=5g sourcetype=diameter | stats count by calling_party | where count > 1000

Defense Evasion Techniques

IMSSI Catcher Stealth

  • 5G Stingray improvements: 5G uses SUPI (concealed via SUCI); attackers force fallback to 4G/3G.
  • Downlink-only operation: Receive-only IMSSI catchers don't page subscribers; harder to detect.
  • Burst operation: Operate for short windows (<30 seconds) to avoid drive-by detection.

Signaling Attack Stealth

  • Slow & low: Pace attacks below signaling firewall threshold.
  • Distributed source: Spread attacks across multiple signaling partners.
  • Use compromised roaming partners: Route through legitimate roaming STPs.

Common Pitfalls

  • Testing in unauthorized environments
  • Ignoring rate limiting (will get blocked)
  • Single-shot testing (real attacks are sustained)
  • Neglecting supply chain
  • Forgetting monitoring/alerting

Reporting and Documentation

Reports should include CVSS scores, MITRE ATT&CK mapping, concrete PoC, business impact, and specific remediation.

Legal and Ethical Considerations

Ensure proper authorization before testing. Document scope in engagement letter. Some attack techniques may violate local laws (e.g., radio transmission without license).

Hacker Laws

LawApplication
Trust but VerifyVerify all outputs; verify all sources
First PrinciplesUnderstand underlying protocols before attacking
Defense in DepthMultiple layers required for robust defense
Assume BreachDesign assuming attacker already inside
Minimize Attack SurfaceReduce unnecessary features/exposure

Learning Resources

Skill supplementary files: payloads.md, test-cases.md

External Resources:

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the 5g 6g Telecom Attack Advanced AI skill do?

Advanced 5G/6G telecom attacks covering 5G Core (SBA) exploitation, IMSI catcher evolution (5G Stingray), SIP/Diameter protocol attacks, Open RAN vulnerabilities, network slicing abuse, and early 6G research vectors (THz comms, AI-native air interface).

Why use 5g 6g Telecom Attack Advanced on TypingMind?

Because you install it once and use it with any model. 5g 6g Telecom Attack Advanced is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install 5g 6g Telecom Attack Advanced in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/brucesongs/kali-claw/tree/main/skills/5g-6g-telecom-attack-advanced. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use 5g 6g Telecom Attack Advanced?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with 5g 6g Telecom Attack Advanced?

As many as you like. As long as a model supports skills, you can use 5g 6g Telecom Attack Advanced with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the 5g 6g Telecom Attack Advanced AI skill free?

Yes. It is published on GitHub by brucesongs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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