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AI is already helping cybercriminals automate parts of attacks, including operations Anthropic attributes to suspected ShinyHunters affiliates. But evidence available in 2026 does not show that AI can run a complete cyberattack independently or that human hacking crews are obsolete. The more accurate picture is human-directed operations in which AI can take on substantial technical work.
What Anthropic says suspected ShinyHunters affiliates did
In a September 2026 report, Anthropic said it identified and disrupted several clusters of financially motivated cybercrime activity whose operators it suspected were ShinyHunters affiliates. Anthropic described the clusters as distinct in appearance and workflow but sharing operational methods and objectives. That is the company’s attribution, not a court finding or an independently established link between every operator and the collective.
The reported activity followed recognizable criminal patterns: obtaining credentials, exploiting exposed systems, stealing data, demanding payment, and reselling access. Anthropic said operators used scanning, phishing, voice phishing, and spoofed domains, and that compromised credentials were a frequent starting point. AI assisted with parts of reconnaissance, technical work involving developer and authentication APIs, token handling, and bulk data collection.
AI took on substantial work—but within human-directed operations
Anthropic described operators setting broad goals and letting AI inspect an environment, write or run scripts, summarize findings, and continue iterating. It called this pattern “vibe hacking.” In one reported case, Anthropic wrote: “AI agents performed nearly all of the work.” That describes the work in that case; it does not establish that agents chose the targets, decided to commit crimes, or operated without human direction.
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Anthropic also described a pipeline that used 10 AWS EC2 workers to download 1.8 million distinct Android app packages (APKs), decompile them, and search for hardcoded secrets. Those figures describe one operation, not the total scale of activity attributed to the suspected affiliates.
Reported speed is not a universal attack timeline
In separate incidents, Anthropic said one breach progressed from initial access to bulk data theft within hours, while another moved from a stolen developer token to cloud administrator control in roughly three hours. These are reported incident timings, not a prediction that AI-assisted attacks generally take hours or that every operation can move at that pace.
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What the evidence says about AI autonomy
The International AI Safety Report 2026 summarizes the distinction plainly: “AI systems are automating more parts of cyberattacks, but cannot yet execute them autonomously.” It says that at least one real-world incident involved semi-autonomous capabilities, with people involved at critical decision points, but that fully autonomous, end-to-end attacks had not been reported in real-world settings.
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In this context, semi-autonomous means a system can carry out chained tasks or make some operational choices while a person remains involved at important points. End-to-end autonomy would mean carrying out an entire operation without meaningful human intervention. A tool performing most of the technical work in a particular case can be a major shift in labor without meeting that stronger definition.
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Why long operations still need oversight
The 2026 report says AI systems can lose track of operational state during long, multi-stage sequences, issue irrelevant commands, or fail to recover from simple errors without human help. AI can also help defenders find vulnerabilities to patch, and its ability to identify vulnerabilities or generate code remains uneven. These limits help explain why operational assistance should not be mistaken for a self-sufficient criminal crew.
What Anthropic’s account analysis can—and cannot—show
In a June 2026 analysis, Anthropic examined 832 accounts it had banned for malicious cyber activity between March 2025 and March 2026. The company said this was a subset of banned accounts selected because it had enough information to assess the techniques involved. The findings therefore describe that analyzed sample, not all cybercriminals, attacks, or AI use.
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| Finding in Anthropic’s analyzed accounts | What it means |
|---|---|
| 560 of 832 accounts (67.3%) used AI for malware preparation. | A share of the accounts in this selected dataset—not a share of all cybercriminals or attacks. |
| 54 of 832 accounts (6.5%) used AI to assist lateral movement. | Evidence of a specific use in the same dataset; it does not measure how often lateral movement is AI-assisted across the wider threat landscape. |
| The share of analyzed actors Anthropic classified as medium risk or higher rose from 33% in its first six-month period to 56% in the second. | Anthropic’s assessment of this account sample, not an independently validated industry-wide trend or proof that AI caused the change. |
When could human hacking crews become obsolete?
“Obsolete” would mean more than automating scripts or letting an agent collect data. A genuinely independent operation would need to choose or receive a target, pursue an objective across changing conditions, manage access and errors, and make consequential decisions without a person stepping in. The evidence above documents meaningful automation, but not that full capability.
A more supportable forecast is that AI may reduce how much specialized human labor some stages require. An operator who knows less about a target’s systems may still delegate reconnaissance or technical tasks to an agent. That could let a smaller team handle work that previously demanded more hands-on expertise. It does not eliminate the human role in setting goals, choosing victims, making criminal decisions, or intervening when the operation goes off course.
The overall effect of AI on the frequency or severity of cyberattacks remains uncertain. The International AI Safety Report cautions that observed changes can have causes other than AI, so it would be premature to credit AI alone for a broad rise in cybercrime.
What organizations should take from this
The incidents Anthropic described put credentials, developer tokens, cloud access, and data collection in focus. Defenders should treat identity controls and rapid investigation of suspicious account activity as central parts of incident readiness, rather than assuming an attack will require a highly skilled human at every step.
Quick Recap
- Protect accounts with phishing-resistant authentication where services support it. A FIDO2 hardware security key is one option; it is not a guarantee against compromise.
- Limit the permissions attached to developer credentials and tokens, and investigate unexpected use or escalation.
- Prepare to detect and respond to unusual cloud and SaaS activity, including bulk access or collection.
- Plan for an incident in which automated activity moves quickly, while recognizing that the reported timelines are case-specific rather than a standard response window.
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