E mail safety has at all times been a cat-and-mouse recreation. Viruses are invented, and antivirus software program is invented to catalog recognized viruses and detect their presence in e mail attachments and URLs. As viruses morphed into extra subtle types of malware, cybersecurity instruments tailored to have the ability to scan for and detect these new threats. Phishing grew to become the following area, giving start to new instruments in addition to a complete new class of protection referred to as safety consciousness coaching. Now, the dangerous guys are attacking AI agents to bypass present safety guardrails.
“AI assistants, copilots, and brokers considerably develop the enterprise assault floor in ways in which conventional safety architectures weren’t designed to deal with,” mentioned Todd Thiemann, a cybersecurity analyst at analysis agency Omdia.
Enter a collection of AI-based options for Proofpoint Prime Threat Protection that have been launched on the firm’s Proofpoint Shield 2025 occasion in September. They thwart the efforts of hackers to subvert the actions of AI brokers by scanning for potential threats earlier than e mail messages arrive at an inbox.
Conventional Strategy to E mail Safety
Most e mail safety instruments are designed to identify recognized dangerous alerts like suspicious hyperlinks, pretend domains that look actual, or attachments carrying malware. This method works nicely towards typical phishing, spam, and recognized exploits. However cybercriminals are actually going after the numerous AI assistants and AI brokers which have turn out to be embedded within the office.
They do that by making the most of prompts (questions or instructions in textual content or code kind) that information AI models and AI brokers to both produce related responses or execute sure duties. More and more, emails carry hidden, malicious prompts that use invisible textual content or particular formatting designed to trick generative AI instruments like Microsoft Copilot and Google Gemini into taking unsafe actions, similar to exfiltrating information or bypassing safety checks.
“Immediate injections and different AI-targeted exploits characterize a brand new class of assaults that use text-based payloads that manipulate machine reasoning fairly than human conduct,” mentioned Thiemann.
Daniel Rapp, Chief AI and Information Officer at Proofpoint, offered an instance: The usual used for e mail messages referred to as RFC-822 lays out the usage of headers, plain textual content, and HTML. Not all of that is seen to a person. Attackers make the most of this by embedding directions in messages which might be invisible to people however totally readable by an AI agent. When AI processes the textual content, the embedded directions are inadvertently executed. This will result in information being exfiltrated or system conduct being altered or corrupted. Legacy filters in search of malware or malformed hyperlinks see nothing amiss.
Daniel Rapp, Chief AI and Information Officer at Proofpoint.Proofpoint
“In current assaults we’re seeing circumstances the place the HTML and plain textual content model are utterly completely different,” mentioned Rapp. “The e-mail shopper renders the HTML model whereas invisible plain textual content accommodates a immediate injection that may be picked up and presumably acted on by an AI system.”
There are two the reason why this technique is proving efficient: First, if an AI assistant has entry to an inbox, it might probably robotically act on an e mail the moment it arrives. Second, Rapp mentioned the literal nature of AI brokers makes them prone to phishing and different social engineering tips. A human may assume twice about sending cash to a Nigerian checking account. An AI agent may blindly perform a command to take action.
What differentiates the Proofpoint method is that the corporate scans emails earlier than they hit inboxes. It’s had loads of observe. The corporate scans 3.5 billion emails day-after-day, one third of the worldwide complete. As well as, it scans near 50 billion URLs and three billion attachments day by day. That is executed inline i.e., whereas the e-mail is touring from the sender to the recipient.
“We now have positioned detection capabilities immediately within the supply path, which implies latency and effectivity are vital,” mentioned Rapp.
This crucial degree of pace is completed by coaching smaller AI fashions particularly on detection, based mostly on examples and the foundational information of a giant language mannequin (LLM). For instance, OpenAI’s GPT-5 is estimated to have as many as 635 billion parameters. Wading by means of that quantity of information for each e mail isn’t possible. Proofpoint has fine-tuned its fashions all the way down to about 300 million parameters. It distills and compresses its fashions to achieve low-latency, in-line efficiency with out sacrificing detection constancy. It additionally updates these fashions each 2.5 days to have the ability to successfully interpret the intent of the message itself, not simply scan for indicators. On this means, it spots hid immediate injections, malicious directions, and different AI exploits earlier than supply.
“By stopping assaults pre-delivery, Proofpoint prevents person compromise and AI exploitation,” mentioned Rapp. “Our secure email gateway can see emails and stop threats before they hit the inbox.”
As well as, Proofpoint makes use of an ensemble detection structure. As an alternative of counting on a single detection mechanism, it combines tons of of behavioral, reputational, and content-based alerts to get round assault vectors which may navigate their well past one methodology.
AI Modifications the Safety Recreation
AI brokers are being rolled out throughout the enterprise and shopper panorama. Sadly, the frenzy to capitalize on AI’s potential typically relegates safety to an afterthought. The dangerous guys know this. They’re AI-enabling their cybercrime methods and applied sciences to good the artwork of phishing for the AI agent period.
“Safety tooling should evolve from detecting recognized dangerous indicators to decoding intent for people, machines, and AI brokers,” mentioned Thiemann. “Approaches that establish malicious directions or manipulative prompts pre-delivery, ideally utilizing distilled AI fashions for low-latency inline safety, handle a major hole in at present’s defenses.”
Proofpoint is forward of the pack with the function out of those capabilities. Count on different cybersecurity distributors to observe go well with within the coming months. By that point, nonetheless, what different AI-borne menace will emerge?
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