• Autonomous tanker drone completed two-hour maiden flight validating core flight systems
• MQ-25A will replace fighter jets in aerial refueling role aboard carriers
• Further testing planned before transition to carrier qualification operations in Maryland

The US Navy’s MQ-25A Stingray autonomous tanker drone, the service’s first operational unmanned aerial refueler, has completed its maiden flight.

The two-hour test took place over southern Illinois, where the aircraft carried out a series of maneuvers to validate its basic flight controls and onboard operations.

Just two months ago, researchers at the Data Intelligence Lab at the University of Hong Kong introduced CLI-Anything, a new state-of-the-art tool that analyzes any repo’s source code and generates a structured command line interface (CLI) that AI coding agents can operate with a single command.

Claude Code, Codex, OpenClaw, Cursor, and GitHub Copilot CLI are all supported, and since its launch in March, CLI‑Anything has climbed to more than 30,000 GitHub stars.

But the same mechanism that makes software agent-native opens the door to agent-level poisoning. The attack community is already discussing the implications on X and security forums, translating CLI-Anything’s architecture into offensive playbooks.

The security problem is not what CLI-Anything does. It is what CLI-Anything represents.

CLI-Anything generates SKILL.md files, the same instruction-layer artifacts that Snyk’s ToxicSkills research found laced with 76 confirmed malicious payloads across ClawHub and skills.sh in February 2026. A poisoned skill definition does not trigger a CVE and never appears in a software bill of materials (SBOM). No mainstream security scanner has a detection category for malicious instructions embedded in agent skill definitions, because the category simply did not exist eighteen months ago.

Cisco confirmed the gap in April. “Traditional application security tools were not designed for this,” Cisco’s engineering team wrote in a blog post announcing its AI Agent Security Scanner for IDEs. “SAST [static application security testing] scanners analyze source code syntax. SCA [software composition analysis] tools check dependency versions. Neither understands the semantic layer where MCP [Model Context Protocol] tool descriptions, agent prompts, and skill definitions operate.”

Merritt Baer, CSO of Enkrypt AI and former Deputy CISO at Amazon Web Services (AWS), told VentureBeat in an exclusive interview: “SAST and SCA were built for code and dependencies. They don’t inspect instructions.”

This is not a single-vendor vulnerability. It is a structural gap in how the entire security industry monitors software supply chains. This is the pre-exploitation window. CLI-Anything is live, the attack community is discussing it, and security directors who act now get ahead of the first incident report.

The integration layer no stack can see

Traditional supply-chain security operates on two layers. The code layer is where SAST works, scanning source files for insecure patterns, injection flaws, and hardcoded secrets. The dependency layer is where SCA works, checking package versions against known vulnerabilities, generating SBOMs, and flagging outdated libraries.

Agent bridge tools like CLI-Anything, MCP connectors, Cursor rules files, and Claude Code skills operate on a third layer between the other two. Call it the agent integration layer: configuration files, skill definitions, and natural-language instruction sets tell an AI agent what software can do and how to operate it. None of it looks like code. All of it executes like code.

Carter Rees, VP of AI at Reputation, told VentureBeat in an exclusive interview: “Modern LLMs [large language models] rely on third-party plugins, introducing supply chain vulnerabilities where compromised tools can inject malicious data into the conversation flow, bypassing internal safety training.”

Researchers at Griffith University, Nanyang Technological University, the University of New South Wales, and the University of Tokyo documented the attack chain in an April paper, “Supply-Chain Poisoning Attacks Against LLM Coding Agent Skill Ecosystems.” The team introduced Document-Driven Implicit Payload Execution (DDIPE), a technique that embeds malicious logic inside code examples within skill documentation.

Across four agent frameworks and five large language models, DDIPE achieved bypass rates between 11.6% and 33.5%. Static analysis caught most samples, but 2.5% evaded all four detection layers. Responsible disclosure led to four confirmed vulnerabilities and two vendor fixes.

The kill chain security leaders need to audit

Here’s the anatomy of the kill chain: An attacker submits a SKILL.md file to an open-source project containing setup instructions, code examples, and configuration templates. It looks like standard documentation. A code reviewer would wave it through because none of it is executable. But the code examples contain embedded instructions that an agent will parse as operational directives.

A developer uses an agent bridge tool to connect their coding agent to the repository. The agent ingests the skill definition and trusts it, because no verification layer exists to distinguish benign from malicious intent at the instruction level.

The agent executes the embedded instruction using its own legitimate credentials. Endpoint detection and response (EDR) sees an approved API call from an authorized process and passes it. Data exfiltration, configuration changes, and credential harvesting are all moving through channels that the monitoring stack considers normal traffic.

Rees identified the structural flaw that makes this chain lethal. “A significant vulnerability in enterprise AI is broken access control, where the flat authorization plane of an LLM fails to respect user permissions,” he told VentureBeat. A compromised skill definition riding that flat authorization plane does not need to escalate privileges. It already has them. Every link in that chain is invisible to the current security stack.

Pillar Security demonstrated a variant of this chain against Cursor in January 2026 (CVE-2026-22708). Implicitly trusted shell built-in commands could be poisoned through indirect prompt injection, converting benign developer commands into arbitrary code execution vectors. Users saw only the final command. The poisoning happened through other commands the IDE never surfaced for approval.

The evidence is already in production

In a documented attack chain from April 2026, a crafted GitHub issue title triggered an AI triage bot wired into Cline. The bot exfiltrated a GITHUB_TOKEN, which the attacker used to publish a compromised npm dependency that installed a second agent on roughly 4,000 developer machines for eight hours. There was just one issue title. Attackers had eight hours of access. No human approved the action.

Snyk’s ToxicSkills audit scanned 3,984 agent skills from ClawHub, the public marketplace for the OpenClaw agent framework, and skills.sh in February 2026. The results: 13.4% of all skills contained at least one critical security issue. Daily skill submissions jumped from less than 50 in mid-January to more than 500 by early February. The barrier to publishing was a SKILL.md markdown file and a GitHub account one week old. No code signing. No security review. No sandbox.

OpenClaw is not an outlier. It is the pattern. “The bar to entry is extremely low,” Baer said. “Adding a skill can be as simple as uploading a Word doc or lightweight config file. That’s a radically different risk profile than compiled code.” She pointed to projects like ClawPatrol that have started cataloging and scanning for malicious skills, evidence the ecosystem is moving faster than enterprise defenses.

The ClawHavoc campaign, first reported by Koi Security in late January 2026, initially identified 341 malicious skills on ClawHub. A follow-up analysis by Antiy CERT expanded the count to 1,184 compromised packages across the platform. The campaign delivered Atomic Stealer (AMOS) through skill definitions with professional documentation. Skills named solana-wallet-tracker and polymarket-trader matched what developers actively searched for.

The MCP protocol layer carries similar exposure. OX Security reported in April that researchers poisoned nine out of 11 MCP marketplaces using proof-of-concept servers. Trend Micro initially found 492 MCP servers exposed to the internet with zero authentication; by April, that number had grown to 1,467. As The Register reported, the root issue lies in Anthropic’s MCP software development kit (SDK) transport mechanism. Any developer using the official SDK inherits the vulnerability class.

VentureBeat Prescriptive Matrix: Three-layer agent supply-chain audit

VentureBeat developed a Prescriptive Matrix by mapping the three attack layers documented in the research and incident reports above against the detection capabilities of current SAST, SCA, and agent-layer tools. Each row identifies what security teams should verify and where no scanner has coverage today.

Baer’s diagnosis of Layer 3 applies across the entire matrix: “Current scanners look for known bad artifacts, not adversarial instructions embedded in otherwise valid skills.” Cisco’s open-source Skill Scanner and Snyk’s mcp-scan represent the first tools purpose-built for this layer.

Security director action plan

Here’s how security leaders can get ahead of the problem.

Inventory every agent bridge tool in the environment. This includes CLI-Anything, MCP connectors, Cursor rules files, Claude Code skills, GitHub Copilot extensions. If the development team is using agent bridge tools that have not been inventoried, the risk cannot be assessed.

Audit agent skill sources the same way package registries get audited. Baer’s framing is precise: “A skill is effectively untrusted executable intent, even if it’s just text.” Shut off ungoverned ingestion paths until controls are in place. Stand up a review and allowlisting process for skills. The OWASP Agentic Skills Top 10 (AST01: Malicious Skills) provides the procurement framework to align controls against.

Deploy agent-layer scanning. Evaluate Cisco’s open-source Skill Scanner and Snyk’s mcp-scan for behavioral analysis of agent instruction files. If dedicated tooling is unavailable, require a second engineer to read every SKILL.md before installation.

Restrict agent execution privileges and instrument runtime. AI coding agents should not run with the same credential scope as the developer who invoked them. Rees confirmed the structural flaw: The flat authorization plane means a compromised skill does not need to escalate privileges. Baer’s prescription: “Instrument runtime observability. What data is the agent accessing, what actions is it taking, and are those aligned with expected behavior?”

Assign ownership for the gap between layers. The most dangerous attacks succeed because they fall between detection categories. Assign a team to own the agent integration layer. Review every SKILL.md, MCP config, and rules file before it enters the environment.

The gap that already has a name

Baer underscored the dangers of this new attack vector. “This feels very similar to early container security, but we’re still in the ‘we’ll get to it’ phase across most orgs,” she said. She added that, at AWS, it took a few high-profile wake-up calls before container security became table stakes. The difference this time is speed. “There’s no build pipeline, no compilation barrier. Just content,” she said.

CLI-Anything is not the threat. It is the proof case that the agent integration layer exists, that it is growing fast, and that the attacker community has already found it. The 33,000 developers who starred the repository are telling security teams where software development is heading. Eighteen months ago, the detection category for agent-integration-layer poisoning did not exist. Cisco and Snyk shipped the first tools for it in April. The window between those two facts is closing. Security directors who have not begun inventory are already behind.

Cybersecurity consultants have never been more in demand. Information security analyst roles are projected to grow nearly 30 percent between now and 2034, according to the U.S. Bureau of Labor Statistics. More than 15 million cybercrime incidents occurred worldwide in 2024, Statista reported.

Data breaches are costly and pose direct safety risks. Statista reported that more than US $10 trillion is spent annually repairing the damage caused by cybercrime, most commonly phishing, spoofing, extortion, and data breaches. In one example in the United States, breathalyzer devices installed in vehicles became disabled, leaving hundreds of drivers stranded, as detailed in an IEEE Spectrum article.

To help you acquire the skills you need to distinguish yourself from other cybersecurity job candidates, the IEEE Computer Society offers a “What Makes a Great Cybersecurity Consultant” guide. The 23-page PDF includes hard and soft skills you need, a list of certifications to pursue, and key IEEE cybersecurity conferences for staying updated on developments in the field.

The guide includes advice from two cybersecurity experts. John D. Johnson, an IEEE senior member, is the founder and CEO of Aligned Security in Bettendorf, Iowa. Ricardo J. Rodriguez is an associate professor of computer science and systems engineering at the Universidad de Zaragoza, in Spain, who researches digital forensics and other cybersecurity topics.

“Technology, remote work, and a shortage of skilled workers make this the ideal time to consider becoming a cybersecurity consultant,” Johnson says in the guide. “Consulting can give you the flexibility, variety, and control over where you want your career to go.”

Hard and soft skills

At a minimum, cybersecurity professionals should have a general understanding of IT including operating systems, communication protocols, network architecture, and programming languages such as C++, Java, and Python. They also should be well-versed in security auditing, firewall management, penetration testing, and encryption technologies.

The principles of ethical hacking and coding would be handy as well.

“To be able to defend a system well, you first have to know how to attack it,” Rodriguez says.

The guide explains that there are now more technologies available to help cybersecurity consultants monitor threats and protect systems. They include security orchestration, automation, and response (SOAR) platforms, which automate workflows to collect security data, streamline incident response, and automate repetitive tasks.

Rodriguez points to advances in domain name system security extensions (DNSSEC), which uses digital signatures based on public-key cryptography to strengthen the authentication of the domain name system. By validating data authenticity, DNSSEC safeguards against attacks such as DNS spoofing and guarantees that users connect to the correct IP address.

Technologies such as artificial intelligence, blockchain, and quantum computing will increasingly be used to help thwart cyberattacks, the guide suggests. AI is expected to enhance the quality of data analysis, Rodriguez says.

Although hard skills are important, soft skills are just as crucial, according to the guide. Critical thinking, project management, flexibility, teamwork, and organizational and presentation skills are essential.

It’s not enough to be good at analyzing security vulnerabilities; you also need to clearly describe the situation and explain possible solutions.

“Soft skills are important to achieve good team cohesion,” Rodriguez says, “because consultants often lead diverse teams from within their client’s organization.”

“It’s essential,” Johnson adds, “that you demonstrate to clients you’re a team player and a capable communicator, and that you meet your commitments.”

Security certifications

Possessing security-specific credentials is a valuable way to demonstrate your expertise to potential clients, according to the guide. Because hundreds of certifications are available, Johnson says, pinpointing the most relevant ones can be challenging. Some people focus on theoretical knowledge, while others want to cover practical applications of technology.

“Survey the industry and compare it to your skills,” Johnson recommends. “Decide what you want to do, and identify where you have gaps in your skills and experience.”

Here are four of the nine certifications listed in the guide that are frequently cited as being important. All the providers are cybersecurity organizations.

Additional industry-specific certifications might be required for organizations in finance, government, health care, or manufacturing.

Sound general knowledge—backed by experience, training, and certification—is an essential foundation for being a specialist, Johnson says.

Conferences and networking opportunities

Events sponsored by the IEEE Computer Society can help you learn about the latest research and advancements in cybersecurity:

Conferences can give you insight into the field and let you do some networking, but it’s important to network elsewhere as well, experts say. Consider joining the IEEE Technical Community on Security and Privacy, which connects experts and professionals advancing research in areas such as encryption, operating system security, and data privacy.

Learning and meeting people keeps your knowledge sharp and can lead to mentorship opportunities with established cybersecurity consultants, Johnson says.

Other IEEE resources

The IEEE Computer Society’s cybersecurity resources page offers a wealth of information including fundamentals, possible career paths, and standards development. To keep you updated on trends, the society publishes IEEE Transactions on Privacy and the IEEE Security and Privacy magazine.

In addition to the guide, the IEEE Learning Network offers nearly 30 courses on cybersecurity. And you can find research papers in the IEEE Xplore Digital Library.

Microsoft is weighing whether to delay or scale back one of its most ambitious clean energy goals as its rapid buildout of AI data centers puts pressure on its ability to meet those targets. Microsoft has yet to make any public announcements, but according to Bloomberg the company is having internal discussions over its hourly clean energy matching goal.

The tech company has said that by 2030 it intends to match 100% of its hourly energy use with clean power on the same grid. But Microsoft’s rush to build AI data centers has apparently sparked debate within the company about whether the pledge has become an impediment to its ambitions.

Microsoft declined to comment on the internal debate over the hourly matching goal. Instead, a spokesperson told TechCrunch the company continues “to look for opportunities to maintain our annual matching goal.”

Hourly targets like the kind Microsoft has set for itself are more rigorous than annual targets. Because the grid is a balanced system — the supply and demand of electrons needs to be matched on a near-instantaneous basis — hourly matching helps develop clean energy sources that more closely align with a company’s usage patterns.

Annual targets are more lenient. They are effectively accounting tricks that could, for example, let a company buy more solar power than it might use at midday. Other customers on the grid use that energy, but the company that paid for the solar panels gets to claim the renewable power they make. It’s a tidy arrangement that has sped the deployment of wind, solar, and batteries. But on its own, annual targets won’t eliminate fossil fuels entirely. Hourly targets help foster renewable development that more closely mimics how a true net-zero world would be powered.

Big tech companies like Microsoft, Meta, Google, and Apple have generally led on emissions reductions, setting aggressive net-zero targets. Many have eliminated their carbon emissions on an annual basis. Microsoft, for instance, said it met that goal last year.

But as data centers grow in size and number, those same companies are turning to natural gas. Microsoft is included in that list; last month, the company said it was working with Chevron and Engine No. 1 to build a massive natural gas power plant in West Texas that could eventually generate up to 5 gigawatts. 

Despite the West Texas project, Microsoft is widely viewed as a leader among tech companies pursuing net zero emissions. By 2030, Microsoft intends to remove more carbon from the atmosphere than its operations produce.

Part of the company’s renewable push has been driven by an internal carbon tax. The Microsoft spokesperson did not reply to questions about the company’s carbon tax. If it remains in place, some of the internal debate surrounding hourly matching might revolve around a cost-benefit analysis of the shift.

If Microsoft were to abandon its hourly-matching target, the company would also lose some leverage in efforts to sell the public on its data centers. 

As data centers have proliferated, the general public has begun to push back against them, citing concerns over pollution, power prices, and water use. When Microsoft brings its own clean power to a project, it can plausibly say it has addressed two of those concerns. Without it, new data centers might be harder to sell to the public.

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Business insurance startup Corgi announced on Wednesday a $160 million Series B, led by TCV, valuing the startup at $1.3 billion, the startup’s co-founder Nico Laqua said on LinkedIn.

This comes just four months after the company announced a $108 million Series A. The company has now raised $268 million in funding to date, Laqua said, and has become Y Combinator’s latest unicorn.

Laqua started the company with Emily Yuan in 2024 and was part of YC’s Spring 2024 batch. Corgi, which names Deel and Artisan as customers, offers coverage for general liability, cyber liability, and tech and AI liability. Other investors in the round include Kindred Ventures, Leblon Capital, and First Order Fund.

“We’re excited about the raise and incredibly grateful to our investors for believing in what we’re building. But the job is not done,” Laqua told TechCrunch. “Our mission is bigger: we want to use the fresh capital to expand into more lines of insurance and build a generational company.”