Cisco FMC Critical Auth Bypass Exploited by Espionage, Ransomware Groups

·1 views

A critical authentication bypass vulnerability (CVE-2026-20079, CVSS 10.0) in Cisco's Firewall Management Center allows unauthenticated attackers to execute commands with root privileges by sending a crafted HTTP request to the web interface. Cisco first patched and disclosed the flaw in March 2026, but active exploitation was observed in August 2026 and confirmed by Cisco Talos on 9 September 2026. Three distinct threat clusters exploited the vulnerability, including a group linked to Russian state-sponsored Sandworm deploying a Cyclops Blink variant, and a Qilin ransomware affiliate that used a chained secondary flaw to harvest credentials and encrypt endpoints. CISA added the vulnerability to its Known Exploited Vulnerabilities catalog on 9 September 2026, setting a federal remediation deadline of 12 September 2026. The incident highlights the outsized risk posed by exposed management consoles, as compromising FMC grants attackers control over every firewall the platform manages.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Developer releases open-source local AI proxy daemon with zero telemetry or cloud dependency

A developer has open-sourced the Garza Global Graviton (GGG) Sovereign Edge Daemon, a self-contained background tool designed to give users full control over their local AI data. The daemon runs as an OpenAI-compatible loopback proxy at a local address, meaning all prompts, history, and context remain entirely on the user's own hardware. It includes HMAC-SHA256 cryptographic response branding and a metadata pacer to maintain data integrity under what the developer calls a Sovereign Math Framework. GGG is compatible with popular AI tools such as VS Code's Continue extension, Open WebUI, LM Studio, and Jan, and requires no accounts or cloud connections. The project is publicly available on GitHub, and the developer is inviting community feedback and contributions.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Recent School Grad Builds Python Restaurant Bot as First Coding Project

Dilesh Zingare, a recent 12th-grade graduate, has shared his first Python project and first written article on DEV Community. The project, called 'Soul the Restro Waiter,' is a command-line restaurant simulation that handles menu display, order taking, quantity input, and bill generation. Zingare discovered the platform through online research and decided to document his early coding journey as a step toward becoming a Developer Advocate. He acknowledged his beginner status and openly invited feedback from readers to help him improve. The project marks the start of his self-taught programming path despite a disappointing exam result that initially shook his confidence.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Oracle PL/SQL Exception Handling: Types, Rules, and Code Examples Explained

Oracle PL/SQL exceptions are runtime error conditions that interrupt normal block execution and transfer control to a designated EXCEPTION section for handling. PL/SQL classifies exceptions into three types: predefined Oracle server errors (such as NO_DATA_FOUND and ZERO_DIVIDE), non-predefined server errors that require manual declaration and binding via PRAGMA EXCEPTION_INIT, and user-defined exceptions raised explicitly by developers for custom business logic. Only one exception handler executes per block run, and the WHEN OTHERS clause, if used, must always appear last in the EXCEPTION section. Non-predefined exceptions are linked to specific ORA- error codes at compile time using the PRAGMA compiler directive in the DECLARE section. Understanding these categories and their declaration requirements helps developers write more robust and maintainable PL/SQL code.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

How to Write Structured Prompts for MiniMax H3 AI Video Generation

A practical guide published on DEV Community outlines a structured approach to writing prompts for MiniMax H3, an AI video generation model. The guide argues that effective prompts should function like production specifications, covering subject, action, camera movement, lighting, timing, and audio in separate, purposeful sentences. A key recommendation is to describe motion as a timeline, breaking a clip into timestamped segments to convey what happens between frames rather than just the final image. The guide also advises separating subject motion from camera motion to avoid conflicting instructions, and using precise cinematographic terms such as 'slow dolly-in' instead of vague phrases like 'cinematic camera movement'. These techniques are presented as ways to make AI video prompts easier to debug, reuse, and control across use cases like product reveals, fashion shots, and vehicle videos.

0 comments Read more at DEV Community