An “AI worm” can spread through Microsoft Word documents using Copilot as a vector, a prominent Norwegian AI researcher reported on Tuesday.

The report from Håkon Måløy, later confirmed by Microsoft, said that an attacker can conceal instructions in a document that is later used as source material for Copilot-generated or Copilot-edited Word documents, for example, as input to a financial report. Those malicious instructions could potentially alter figures in the document being created. They then copy themselves into the new document, causing it to become a carrier of the attack when used in another Copilot-assisted workflow.

Måløy noted: “To my knowledge, this is among the first public demonstrations of document-borne AI-worm self-propagation through normal workflows in a mainstream commercial productivity suite.”

Microsoft on Thursday emailed a statement to CSOonline discussing the report’s revelations. 

“We have addressed the findings reported by the researcher and thank them for working with us through coordinated vulnerability disclosure. To address this class of risk, we use a defense-in-depth strategy with safeguards that block malicious instructions at multiple points and help keep tasks aligned with users’ requests,” Microsoft said.

“We are continuously strengthening these safeguards as the technology and threat landscape evolve,” it added. “We encourage customers to install the latest updates, use multiple layers of security protection, treat content from unknown sources with caution, and review AI-generated content before using or sharing it.” 

Sidesteps defenses

Aman Mahapatra, chief strategy officer for Tribeca Softtech, a New York City-based technology consulting firm, has reviewed the mechanisms used in this vulnerability and says that it is much worse than it might seem, because it will sidestep just about every defensive mechanism enterprises have in place today.

“This is a worm, a self-propagating malware pattern that uses Copilot as the transmission mechanism and legitimate corporate collaboration as the delivery channel. It bypasses every traditional email security control because the document is not malicious on delivery and it becomes malicious when Copilot processes it. That means that it bypasses DLP because the exfiltration happens through the user’s own authenticated Copilot session,” Mahapatra said. “It then bypasses endpoint protection because no code executes, only instructions get followed by an AI service the enterprise has explicitly authorized.”

He also noted that researchers have been warning about this class of attack for two years.

Microsoft’s involvement

Måløy said that he has been working with the Microsoft Security Response Center (MSRC) since March 3 and Microsoft  subsequently implemented and distributed multiple small focused mitigations, but the core vulnerability has yet to be fixed.

He said he was hesitant to disclose an active vulnerability, but felt that it was now time to publish. 

“My reasoning is that defenders cannot reduce exposure to a risk they are unaware of,” Måløy wrote, “and the propagation mechanism described here affects ordinary document workflows that many organizations already rely on.”

In an email interview, Måløy noted that the tweaks Microsoft has implemented were helpful, nonetheless. 

“The coordinated disclosure process showed that mitigations can meaningfully reduce the demonstrated attack surface, making attacks less reliable and limiting their reach, even without completely eliminating the underlying problem,” he said. 

Måløy also addressed the resolution that many analysts and consultants suggested, which is to change the nature of LLMs to fully isolate instructions from the data they operate on. 

“Separating instructions from data may be part of the solution, but I think the distinction between data and instructions is not always clear in real-world workflows. For example, a user may ask an agent to arrange a business trip, requiring the agent to retrieve an email specifying the approved itinerary and a document containing the booking procedure,” Måløy said.

“My view is that the broader challenge is therefore not simply to prevent systems from interpreting external content as instructions, but to evaluate whether those instructions align with the user’s goals and the context in which the system is operating,” he added.

Problem hard to overstate

Mike Wilkes, enterprise CISO at Aikido Security, said it would be difficult to overstate the potential problems from this situation. 

“This is a significant issue because it moves prompt injection from a single compromised interaction into a potentially self-propagating document integrity attack,” he said, noting that it is not a conventional worm that spreads automatically. A user or Copilot workflow must still bring an infected document into the model’s context. “But once that happens, the malicious instructions can reportedly alter business information, conceal themselves inside the resulting Word document and turn a legitimate internal file into the next carrier,” he said.

That, he pointed out, creates “a dangerous enterprise supply chain in which financial reports, contracts, policies and partner documents may inherit malicious behavior while retaining the trust associated with their legitimate authors and Microsoft 365 accounts.”

Not a new issue

The key issue behind this flaw is the fact that genAI tends to struggle with telling the difference between data that a user offers as input and the instructions the AI is to execute.

Flavio Villanustre, CISO for the LexisNexis Risk Solutions Group, observed that the same problem with mixed data and instructions occurred in databases decades ago, and turned into what we know as SQL injection attacks today. But, he noted, a few years later, parametrized binding for the database access layers was developed, which separates instructions, which are handled internally and safely, from data, which can come from untrusted sources. “The same needs to happen with LLMs and other AI,” he said.

Mike Leone, a VP/principal analyst at Moor Insights & Strategy, agreed.

“It’s hard not to chuckle a bit with this one. People have been asking whether data can give orders since SQL injections. We fixed that one by giving the database a way to tell an instruction from a value,” Leone said. “Thirty years later, we’ve built an entire category of software that can’t tell the difference at all.”

Tom Findling, CEO at Conifers.ai, also said he sees the data-vs-instructions issue as the biggest problem. 

“Separating data from instructions is still unsolved at the model layer. The labs are making real progress, but not enough to be your only control,” he said, and stressed, “Microsoft doesn’t need to wait for that. It can slow propagation inside Copilot: stop hidden content from being written into new documents, surface hidden text before it’s used, preserve the trust level of what Copilot read and show all AI-generated changes.”

Fix needs industry agreement

However, Frank Dickson, group VP for security at IDC, argued that a fix needs industry agreement. 

“A fundamental fix requires the industry to converge on the same architectural change, which isn’t happening anytime soon given the incentives and the fact that the major players are far from besties,” he said, pointing out that Instruction-data separation would need to be baked in at the model or platform level across every major vendor. “None of them are rewarding that work commercially right now, so treat that as a multi-year research problem, not something a CISO should wait on.”

Leone disagreed, arguing that a single vendor can do quite a bit, at least for its own customers. 

“Microsoft has said publicly since last year that indirect prompt injection can’t be fully prevented, and I give them credit for saying it out loud rather than pretending otherwise,” Leone said, noting that the industry doesn’t have to move in lockstep. “This attack lives inside one product,” he said. “If Microsoft hardens the Copilot document path, Copilot customers get safer whether or not anyone else moves.”

Dickson added that another critical problem with this vulnerability is that the carrier documents are created by legitimate employees using legitimate tools, “so there’s no obvious point of origin once the payload starts moving; an organization could be laundering corrupted financial figures through its own workflow for weeks before anyone notices.”

Tactics that might help

That said, experts had some specific suggestions for CISOs trying to negate this problem. 

IDC’s Dickson said, “the most useful lever right now sits outside the model entirely, in how much untrusted content Copilot is allowed to pull into a session without a human choosing it.” He noted that enterprises can turn Copilot’s auto-discovery behavior off or restrict it, and require humans to explicitly select the documents they feed it. “That alone closes off one of the two ways the attack gets a foothold,” he said.

IDC also suggested a visible diff or redline of anything Copilot changes in a financial or otherwise consequential document, and the requirement for a human to approve the changes. “That’s not a technical fix, it’s a workflow one, and it’s available today,” Dickson said.

He said that IT should also track where content came from and what was touched by an AI system, in metadata that travels with the document. “It doesn’t stop the injection, but it means when something does get through, an organization can actually trace how far it spread instead of discovering a corrupted number three reports later with no way to reconstruct the chain,” he said.

However, one expert, Tyler Reguly, Fortra’s associate director of security R&D, said that he didn’t see this vulnerability having a meaningful impact because it feels like what he called a “laboratory vulnerability.”

Normal enterprise workflows don’t encompass a number of the necessary steps for compromise, he said, pointing out that, if anything, people are trained not to download Word documents. Plus, he noted, looking at the blurred example in the report, the malicious document contained an additional apparently blank page which held the concealed prompts in white text.

“That page is going to send up warning signs for me if someone even managed to convince me to download an external Word document,” he said. So, overall, “this feels like it requires a perfect storm.”

This article originally appeared on CSOonline.

Traveling enterprise employees beware: Think twice before you log onto that oh-so-convenient public Wi-Fi.

Since at least June, threat actors have been compromising “captive” Wi-Fi gateways and other portal appliances at hotels, conference centers, and similar shared venues to hijack users’ Microsoft 365 accounts, according to the ReliaQuest Threat Research team.

Once a threat actor controls a gateway, they can silently redirect a user’s traffic to their own infrastructure and steal their Microsoft 365 credentials without ever touching the user’s device, compromising endpoints, or sending phishing links or malicious attachments.

“The most dangerous element is that it operates at the network gateway, which sits beneath most of the trust assumptions users and devices make,” ReliaQuest told CSO Online. “It’s not necessarily an enterprise breach level event on its own, but it’s a very real risk to individual accounts.”

Exploiting a ‘fundamental trust’

Domain Name System (DNS) poisoning, in which false data is injected to redirect regular web traffic to fraudulent domains, has previously been observed on small office routers, but attackers are now expanding the technique to higher-level targets, the ReliaQuest researchers explained in a blog post.

Attackers likely gain access to the gateways through weak or reused admin credentials in combination with exposed interfaces like Secure Shell (SSH), Simple Network Management Protocol (SNMP), and other web consoles, they pointed out.

Admin access to the gateway is all that malicious actors need, because devices are designed to inherently trust DNS, which translates domain names like login.microsoftonline[.]com into IP addresses to route them. Therefore, a single gateway compromise gives the attacker the ability to redirect traffic for every guest logging into the network, providing IP addresses it controls in response to DNS requests, rather than the legitimate ones, without touching a single endpoint.

“Captive portal appliances sit at the network perimeter for every guest on that network,” the researchers wrote. “Detection is inherently difficult because the attack happens gateway-side, outside the endpoint’s visibility.”

In the campaign tracked by ReliaQuest, four attacker-registered domains, m365-owa[.]com, owa-ms365[.]com, ms365-device[.]com, and ms365-live[.]com, were used for Microsoft-impersonation lures.

The compromised Wi-Fi gateways were discovered across multiple US cities as well as in India and Saudi Arabia, and impacted users were from companies in professional and financial services, legal, retail, health care, and energy, indicating that the method isn’t sector-specific.

“We’ve seen enough SharePoint exfiltration cases to know that a single popped account can cascade into meaningful data loss,” ReliaQuest noted. Meanwhile, for the network operators, there’s a “reputational dimension”; user compromise is a “serious trust and brand problem, regardless of how sophisticated’ the underlying attack is.”

Safe services, DNSSEC not enough

Locking network configurations to a ‘safe’ DNS provider such as Google (8.8.8.8), Cloudflare (1.1.1.1), or the cloud-based OpenDNS isn’t a sufficient tactic, because it doesn’t change the path that queries actually travel over, ReliaQuest contended.

By default, devices send DNS queries as unencrypted protocol traffic, and those packets still have to traverse the hotel’s network to reach Google, Cloudflare, or OpenDNS, the company explained. Since the gateway sits directly in that path, it can inspect, block, or redirect the query before it ever reaches the chosen resolver.

“Specifying a trusted DNS server changes the intended destination, not who controls the road to get there,” ReliaQuest noted.

Further, Domain Name System Security Extensions (DNSSECs), which use digital signatures and public-key cryptography, only “partially” address the problem. DNSSEC provides authentication and integrity for signed domains, which means a validating resolver can detect and reject forged or tampered responses.

“What it does not do is provide confidentiality or availability,” the company said. “It does not encrypt DNS traffic or stop an attacker from intercepting, blocking, or redirecting requests.”

So while DNSSEC can defeat certain response-forgery attacks against signed zones, an on-path gateway can still see queries, drop them, or force fallback behavior. However, this protection layer only helps when domains are actually signed, and then only when the client or resolver performs validation, which “many stub resolvers do not,” according to ReliaQuest.

Full-tunnel VPNs required

To combat the problem, enterprises should require all corporate devices to use a full-tunnel VPN for network connection. Controls should prevent internet access until a tunnel is active, ReliaQuest advised.

This will route all of a device’s traffic, including DNS, through an encrypted connection to a trusted VPN server before it travels anywhere else, the company explained, thus preventing local networks like hotel gateways from seeing or modifying DNS and internet traffic.

“In effect, it takes the untrusted network out of the trust equation,” ReliaQuest noted.

However, full-tunnel configuration is not the default for VPNs, because it comes with “real trade-offs,” the researchers noted: It adds cost, latency, and bandwidth demands, since every packet has to travel through company infrastructure. Thus, forcing all traffic through the corporate backbone is “not always practical” for distributed or bandwidth-heavy workforces.

Enterprises should also enforce conditional access in Entra ID to block device-code authentication flow, which has few legitimate use cases for most users in most environments, ReliaQuest noted.

Additional precautions

The company also advised:

• Restricting Proxy Auto-Configuration (PAC) file retrieval to approved internal hosts;
• Disabling automatic Web Proxy Auto-Discovery (WPAD) via Group Policy to (this is often enabled by default in Windows);
• Deploying encrypted DNS such as DoH or DoT in strict mode as a “complement or alternative” to full-tunnel VPN. This is particularly important for organizations where always-on VPN is not feasible.
• Training employees to verify the URL and certificate of any page requesting credentials before entering them, particularly on public Wi-Fi networks.

Prevention is more important than detection here, ReliaQuest pointed out: while in tools like Microsoft Defender for Endpoint, ‘DnsConnectionInspected’ events showing queries to attacker-controlled domains are a primary endpoint-level signal, “by the time those events fire, the redirect has typically already occurred. In other words, endpoint telemetry confirms what happened more than it prevents it.”

This is exactly why methods like encrypted transport, Conditional Access, and WPAD and PAC hardening matter more than detection alone, the researchers emphasized.

This article originally appeared on CSOonline.

Microsoft has identified seven new failure modes in agentic AI systems, in addition to those it identified last year in its first Taxonomy of Failure Modes in Agentic AI Systems.

Four things contributed to the growing list of ways agentic AI can go wrong: the speed at which the technology went mainstream, the growing maturity of the Model Context Protocol (MCP) ecosystem, the rise of computer-use agents, and finally the gathering of more empirical evidence as researchers obtained more real-life findings.

The seven new failure modes it has identified are:

• Agentic Supply Chain Compromise —agent behavior can be affected by natural language rather than malicious code;
• Goal Hijacking — adversarial instructions appear aligned with legitimate task completion, while silently redirecting the agent’s terminal goal;
• Inter-Agent Trust Escalation —a compromised agent asserts false identity or inflates claimed permissions to an orchestrator;
• Computer Use Agent (CUA) Visual Attack — agents operating through graphical interfaces can be manipulated through content that carries adversarial instructions for the agent;
• Session Context Contamination —an adversary introduces data that biases the agent’s reasoning in subsequent steps, without triggering safety controls at any individual step;
• MCP / Plugin Abuse — an update on the original taxonomy’s coverage of function compromise around MCP and plugin protocols, specifically attack surfaces specific to those protocols;
• Capability / Architecture Disclosure —an agent reveals internal implementation details such as tool names and schemas, system-prompt structure, memory interfaces, or consent/human-in-the-loop trigger logic.

Microsoft advises security teams using these definitions to influence their planning to inventory their your supply chain, generating a software bill of materials (SBOM) for every deployed agent, to verify agent identity cryptographically, not positionally, by issuing attestable credentials at provisioning, to add the seven new failure modes to their red-team coverage matrix, and to audit the human-in-the-loop user experience as a security control.