CyberSE.AI is a daily AI security intelligence and advisory platform for SMBs and AI startups deploying LLMs, AI agents, model APIs, and AI-enabled workflows.

What risks does CyberSE.AI cover?

CyberSE.AI covers prompt injection, indirect prompt injection, AI agent abuse, data leakage, model and supply-chain risk, AI governance, and OWASP-relevant LLM and API security risks.

Secure AI Agent Build

Architect and deploy secure, production-grade LLM agents with hardened system prompts, strict tool isolation, content sanitation layers, and custom orchestrators.

Engagement Methodology

Target Sectors

SaaS Fintech Enterprise Software E-commerce

Common Use Cases & Vulnerability Checks

Autonomous Agent Orchestration
Tool Access Hardening
RAG Pipeline Security
System Prompt Guardrails

Standard Deliverables

Detailed risk surface and model architecture mapping
Exploit scenarios, payload reports, and recreations
Specific prompt guardrails and output sanitizer templates
CISSP/CEH-informed security attestation letter

Schedule Engagement Briefing

In The News

Live Dynamic Threat Proof-Points

We monitor curated channels for live security compromises. Below are recent approved threat intelligence incidents relating to Secure AI Agent Build risk scopes:

Published: 2026-06-03 | Source: thehackernews.com

Unpatched Windows Search URI Vulnerability Lets Attackers Steal NTLMv2 Hashes

The report describes an unpatched Windows search: URI handler issue that can cause a victim system to make an outbound SMB connection and leak the user’s NTLMv2 hash to an attacker-controlled server. Huntress says the flaw uses the same NTLM leakage mechanism as the previously patched Snipping Tool URI issue, and Microsoft declined to issue a fix after responsible disclosure. CyberSE.AI analysis: this is primarily a credential/data leakage risk with downstream relay-attack potential, so defenses should focus on restricting outbound SMB, enforcing SMB signing, and reducing NTLM exposure where possible.

Severity Score: 78/100

Published: 2026-06-03 | Source: securityweek.com

Hackers Target Global Stock Exchange in Espionage Operation

Report facts: attackers gained access to a senior executive’s email account at a major global stock exchange and exfiltrated data for roughly 150 days, with the operation assessed as likely espionage. CyberSE.AI analysis: this is best categorized as data leakage because the core impact is long-term unauthorized access and theft of sensitive information, which would be especially damaging if any AI-enabled workflows, inbox automation, or decision-support systems were exposed. Security priorities should include access control hardening, mailbox and identity monitoring, and review of any AI systems that may ingest or route executive communications.

Severity Score: 90/100

Published: 2026-05-30 | Source: Cycode

Top AI Security Vulnerabilities to Watch out for in 2026

The Cycode article identifies prompt injection as one of the most prominent and commonly cited AI security vulnerabilities in 2026, describing how attackers craft inputs to override intended model behavior across many AI applications.[5] The piece focuses on general AI security controls and attack patterns, not on any single breach or incident, framing prompt injection as a systemic weakness that must be addressed in architecture and operations. From a CyberSE.AI perspective, this directly implicates the need for secure agent design (strict role/system prompts, input/output mediation, least-privilege tools) and targeted business-logic reviews to find where instructions can be subverted. Ongoing AI red teaming is also warranted to continuously probe for new injection techniques against deployed agents and RAG workflows before adversaries do.

Severity Score: 88/100