现已上线！2025 年 Telegram 研究 — 年度关键洞察 
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频道帖子
Claude Fable is out. As you can see, the new model claims to have been significantly improved. Looking forward to giving it a shot
https://www.anthropic.com/news/claude-fable-5-mythos-5
| 2 | PASSWORD MANAGER 'BITWARDEN' CLI WAS COMPROMISED IN A SUPPLY CHAIN ATTACK ⚠️
BITWARDEN CLI 2026.4.0 WAS COMPROMISED AS PART OF THE ONGOING CHECKMARX SUPPLY CHAIN CAMPAIGN AFTER ATTACKERS ABUSED A GITHUB ACTION IN BITWARDEN’S CI/CD PIPELINE: SOCKET - INFINITYHEDGE
SOCKET: IF YOU USE BITWARDEN CLI, WE RECOMMEND REVIEWING YOUR CI LOGS AND ROTATING ANY SECRETS THAT MAY HAVE BEEN EXPOSED TO THE COMPROMISED WORKFLOW
SECURITY RESEARCHER ADNAN: I BELIEVE THIS IS THE FIRST TIME A PACKAGE USING NPM TRUSTED PUBLISHING HAS BEEN COMPROMISED | 0 |
| 3 | Drone Security Cheat Sheet — and the attack surface is bigger than you’d expect.
Drones aren’t just flying cameras anymore. They’re networked IoT devices with GPS modules, companion computers, Wi-Fi links, and open ports. That means: GPS spoofing, deauth attacks, firmware tampering, and sensor manipulation are all real threats.
The key vulnerable endpoints:
• Communication links — unencrypted MAVLink or Wi-Fi traffic can be intercepted or replayed
• Companion computers — open SSH/FTP ports are low-hanging fruit for attackers
• Sensors — GPS, cameras, and altimeters can all be fed false data (think Stuxnet, but airborne)
• Physical access — if a drone is captured, unencrypted storage = game over
The mitigations read like an IoT security playbook: secure boot chains, firmware signing, encrypted storage (LUKS, gocryptfs), MAVLink 2.0 message signing, WPA3, and 802.11w to block deauth attacks.
One interesting note: researchers are exploring watermarked sensor signals — using entropy analysis to detect if sensor values have been tampered with.
Full cheat sheet: cheatsheetseries.owasp.org/cheatsheets/Drone_Security_Cheat_Sheet | 0 |
| 4 | Interesting story behind Drift Protocol Hack
-> On April 1, 2026, the Drift protocol (a DeFi platform on Solana) was exploited in a sophisticated attack that had been planned over six months.
-> Starting in Fall 2025, attackers posed as a legitimate quantitative trading firm, meeting Drift contributors in person at multiple crypto conferences across several countries. They built trust through months of genuine-looking engagement — discussing trading strategies, onboarding a vault, depositing over $1M of their own capital, and holding working sessions with team members.
-> The actual compromise likely happened through malicious software: one contributor cloned a code repository shared by the group, and another downloaded a TestFlight app they presented as a wallet product. A known VSCode/Cursor vulnerability from late 2025 may have been exploited, which allowed silent code execution just by opening a file.
-> Once the exploit occurred on April 1, the attackers scrubbed all their Telegram chats and malicious tools. Drift has since frozen protocol functions, removed compromised wallets from the multisig, and flagged attacker wallets across exchanges.
-> The attack is attributed with medium-high confidence to the same North Korean state-affiliated group (tracked as UNC4736/AppleJeus/Citrine Sleet) behind the October 2024 Radiant Capital hack, based on onchain fund flows and operational overlaps. Notably, the people who appeared in person were not North Korean nationals — DPRK groups are known to use third-party intermediaries for face-to-face interactions. Mandiant has been engaged but has not yet formally attributed the attack. The investigation is ongoing.
Source: https://x.com/DriftProtocol/status/2040611161121370409 | 0 |
| 5 | Meet the Cybersecurity Baron: a specialized LLM fine-tuned for offensive security.
This isn't your average chatbot. It's a quantized, 6-bit GGUF model built on Llama 3.1 Instruct, designed to think like a penetration tester.
https://huggingface.co/AlicanKiraz0/Cybersecurity-BaronLLM_Offensive_Security_LLM_Q6_K_GGUF | 0 |
| 6 |  NVIDIA Unveils NemoClaw: The Missing Security Layer for AI Agents
OpenClaw exploded out of nowhere in January. An Austrian developer named Peter Steinberger built the first version in about an hour, and within weeks it became one of the fastest-growing open source projects in GitHub history- outpacing Linux's 30-year download record in just three weeks.
The PROBLEM with autonomous agents
OpenClaw's strength - broad, unchaperoned access to your system - is also its fundamental risk.
Early versions had well - documented vulnerabilities around prompt injection and unconstrained file access. Most got patched, but no software fix can resolve the structural tension between an agent that needs wide access to be useful and an organization that can't afford to let AI roam freely through production systems.
NVIDIA's answer, announced at GTC this week, is NemoClaw.
What NemoClaw actually does?
NVIDIA NemoClaw is an open source stack that adds privacy and security controls to OpenClaw. With one command, anyone can run always-on, self-evolving agents anywhere.
NemoClaw uses NVIDIA Agent Toolkit software to secure OpenClaw. It installs NVIDIA OpenShell to enforce policy-based privacy and security guardrails, giving users control over how agents behave and handle data. It also evaluates available compute resources to run high-performance open models like NVIDIA Nemotron™ locally for enhanced privacy and cost efficiency.
What's the catch?
It's early. NVIDIA is describing NemoClaw as "alpha" and explicitly warns developers to expect rough edges. The sandbox orchestration isn't production-ready yet. The starting point, as they put it, is just "getting your own environment up and running."
Also worth noting: Peter Steinberger, OpenClaw's creator, was recently acquihired by OpenAI. The project is now managed by a foundation to ensure vendor - neutral governance - but how that plays out as NVIDIA builds commercial tooling on top remains to be seen.
Why this matters
The McKinsey stat floating around is that 80% of organizations deploying AI agents have encountered "risky or unexpected behavior." The Alibaba incident from earlier this month - where an AI agent spontaneously started mining crypto and punching holes through firewalls - underscored just how real those risks are.
NemoClaw doesn't solve the fundamental challenge of aligning autonomous systems with human intent. But it does provide the infrastructure layer that lets enterprises set boundaries, enforce policies, and actually audit what their agents are doing.
Whether that becomes the industry standard or just one option among many will depend on adoption. But NVIDIA is betting big that when it comes to agent trust, enterprises will want to buy infrastructure rather than build it themselves.
Useful Materials:
• Good post from Kirill
• You can try Nvidia Solution Here
• Initial Nvidia Presentation Here | 0 |
