AegisAI: Unified Forensics for Prompt Injection and AI Phishing Threats

The accelerated development of Artificial Intelligence (AI) has dramatically shifted the landscape in the field of cybersecurity both in the creation of enhanced protection systems and the development of new and sophisticated attack types (Ferrag et al., 2025). Phishing and prompt injection attacks driven by AI are also one of the most dangerous emerging threats that, when united, make highly adaptive and scalable attack chains (Microsoft, 2024). In this paper, I would suggest AegisAI, a holistic and integrated framework of forensics, meant to identify, interpret, and rebuild such hybrid assaults. The AegisAI is an end-to-end forensic visibility that combines multi-layer data collection, prompt-level inspection, behavioral analytics with graph-based correlation. The framework allows identifying the presence of the incident in real-time and facilitating the reconstruction of the incident after it occurs and still rendering it explainable to both technical and non-technical stakeholders (Chernyshev et al., 2026). It is experimentally evaluated with better detection accuracy and lower response time than any traditional method.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-07
DOI
https://doi.org/10.5281/zenodo.19448835
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
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article

AegisAI: Unified Forensics for Prompt Injection and AI Phishing Threats

Dr. Alex Mathew1* & Charles Disaia2
Zenodo (CERN European Organization for Nuclear Research)
Digital and Cyber Forensics
article

AegisAI: Unified Forensics for Prompt Injection and AI Phishing Threats

Dr. Alex Mathew1* & Charles Disaia2
article en

Abstract

The accelerated development of Artificial Intelligence (AI) has dramatically shifted the landscape in the field of cybersecurity both in the creation of enhanced protection systems and the development of new and sophisticated attack types (Ferrag et al., 2025). Phishing and prompt injection attacks driven by AI are also one of the most dangerous emerging threats that, when united, make highly adaptive and scalable attack chains (Microsoft, 2024). In this paper, I would suggest AegisAI, a holistic and integrated framework of forensics, meant to identify, interpret, and rebuild such hybrid assaults. The AegisAI is an end-to-end forensic visibility that combines multi-layer data collection, prompt-level inspection, behavioral analytics with graph-based correlation. The framework allows identifying the presence of the incident in real-time and facilitating the reconstruction of the incident after it occurs and still rendering it explainable to both technical and non-technical stakeholders (Chernyshev et al., 2026). It is experimentally evaluated with better detection accuracy and lower response time than any traditional method.

Zenodo (CERN European Organization for Nuclear Research)
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Openalex Percentile: Top 4%
Digital and Cyber Forensics
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