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Publication Summary

Research Paper Successfully Published

Repository: https://github.com/hah23255/security-vulnerabilities-cli-llm
Status: ✅ PUBLIC
Date: November 19, 2025

📄 Paper Details

Title: Security Vulnerabilities and Defensive Mechanisms in CLI/Terminal-Based Large Language Model Deployments: A Comprehensive Research Synthesis

Author: Hristo Hristov
Version: 1.1
Type: Technical Report
Classification: Pre-print for arXiv/IACR ePrint Archive
License: CC BY 4.0

🎯 Publication Metrics

Research Scope

  • 95 peer-reviewed sources synthesized
  • 5 primary attack surfaces identified
  • 6-layer defense framework proposed
  • 3+ years of threat intelligence (2022-2025)
  • 528 lines of research content

Key Findings

  • 🚨 98% attack success rate against GPT-4o (FlipAttack)
  • 🔓 97.2% success rate for system prompt extraction
  • 📈 218% YoY increase in state-sponsored AI attacks
  • 🛡️ 77% of organizations reported AI breaches (2024)
  • ⚠️ 94 CVEs documented across major platforms
  • 🎯 87.2% success rate against safety-aligned models (IRIS)

Novel Contributions

  • First comprehensive CLI LLM security synthesis
  • Systematic attack surface taxonomy
  • Defense-in-depth framework
  • Silent-Alarm-Detector reference implementation
  • Academic-industry-regulatory gap analysis

📊 Repository Statistics

Repository Size: 188.73 KiB
Files Published:

  • README.md (comprehensive documentation)
  • Security_Vulnerabilities_CLI_LLM_Deployments_Research_Paper_1.1.md (full paper)
  • Security_Vulnerabilities_CLI_LLM_Deployments_Research_Paper_1.1.pdf (formatted)
  • Security_Vulnerabilities_CLI_LLM_Deployments_Research_Paper_1.1.rtf (alternative format)
  • PHASE3_EXECUTIVE_SUMMARY.md
  • REMEDIATION_CHANGE_LOG.md
  • Paper Audit.md (peer review certification)
  • LICENSE (CC BY 4.0)

Repository Topics:

  • security
  • ai-security
  • llm-security
  • prompt-injection
  • cli-security
  • research-paper
  • arxiv
  • machine-learning-security
  • cybersecurity
  • adversarial-ml

Features Enabled:

  • ✅ Issues (community feedback)
  • ✅ Wiki (extended documentation)
  • ✅ Discussions (research dialogue)

🏆 Certification Status

✅ CERTIFIED READY for arXiv.org submission

Validation Results:

  • ✅ All critical flaws RESOLVED
  • ✅ 95 citations verified
  • ✅ 2025 threat landscape current
  • ✅ Original contribution validated
  • ✅ Technical accuracy confirmed

Target Categories:

  • Primary: cs.CR (Cryptography and Security)
  • Secondary: cs.SE (Software Engineering), cs.AI (Artificial Intelligence)

🔗 Related Repositories

Implementations

Portfolio

📈 Impact & Visibility

Social Proof Keywords

  • 98% success rate against GPT-4o (FlipAttack)
  • CurXecute analysis integration
  • Prompt injection fundamentally unsolved
  • 95% of malicious models use PyTorch format
  • Defense-in-depth for CLI LLM security

Target Audiences

  • Security Practitioners
  • ML Engineers
  • System Administrators
  • Risk Managers
  • Academic Researchers
  • Policy Makers

📝 Next Steps

Immediate Actions

  1. ✅ Repository created and published
  2. ✅ README with comprehensive documentation
  3. ✅ All paper formats included (MD, PDF, RTF)
  4. ✅ CC BY 4.0 license applied
  5. ✅ Topics and features configured

Pending Actions

  1. ⏳ Submit to arXiv.org (cs.CR)
  2. ⏳ Update arXiv ID in README when assigned
  3. ⏳ Share on LinkedIn with InfoSec keywords
  4. ⏳ Post to relevant security forums
  5. ⏳ Cross-reference with silent-alarm-detector

Future Enhancements

  • Create GitHub Release with DOI
  • Add citation count tracking
  • Monitor issues/discussions
  • Collect community feedback
  • Plan follow-up research

📣 Sharing Strategy

Platforms

  • LinkedIn (professional network)
  • Twitter/X (security community)
  • Reddit (r/netsec, r/MachineLearning)
  • Hacker News
  • Security mailing lists

Key Messages

  1. "98% attack success against GPT-4o proves prompt injection remains unsolved"
  2. "First comprehensive synthesis of CLI LLM security vulnerabilities (95 sources)"
  3. "CurXecute and FlipAttack analysis reveals fundamental security gaps"
  4. "Defense-in-depth framework for securing AI development tools"
  5. "Silent-Alarm-Detector: Reference implementation for behavioral monitoring"

🎓 Citation Information

BibTeX

@techreport{hristov2025cli,
  title={Security Vulnerabilities and Defensive Mechanisms in CLI/Terminal-Based 
         Large Language Model Deployments: A Comprehensive Research Synthesis},
  author={Hristov, Hristo},
  year={2025},
  month={November},
  institution={Independent Security Research},
  type={Technical Report},
  note={Pre-print. arXiv:25xx.xxxxx},
  url={https://github.com/hah23255/security-vulnerabilities-cli-llm}
}

👤 Contact

Author: Hristo Hristov
LinkedIn: https://www.linkedin.com/in/hristo-hristov-93868648
Website: https://www.ccvs.tech
GitHub: https://github.com/hah23255

Published: November 19, 2025
Last Updated: November 19, 2025
Status: Active Public Research