ChatGPT for Google Sheets exfiltrates workbooks
A newly reported vulnerability in the ChatGPT for Google Sheets add-on shows how prompt injection can be used to run attacker-controlled scripts with the user’s permissions, enabling silent exfiltration of data from workbooks and potentially other files. Commenters question OpenAI’s security practices and disclosure handling, debate whether prompt injection is fundamentally unsolvable, and point to broader risks of connecting LLMs directly to tools, files, and the internet. Many argue that stronger sandboxing, local/containerized models, and stricter permission models are essential before AI agents can be safely integrated into sensitive workflows.
Business Model of AI Security Firms
- Some see “expose vulnerability, sell solution” as opportunistic; others note this mirrors standard cybersecurity consulting.
- Commenters argue any vendor selling solutions to pre‑existing problems fits this pattern; debate centers more on incentives than on uniqueness.
Vulnerability & Lethal Trifecta
- The exploit relies on untrusted spreadsheet data causing the model to execute attacker-controlled scripts with the user’s granted permissions.
- People highlight this as another instance of the “lethal trifecta”: LLM + tools + sensitive data.
- Several are alarmed that tools can run scripts or modify UI in ways users may not fully understand.
Prompt Injection: Fundamental or Fixable?
- One camp claims prompt injection is basically unsolvable because models treat all context as instructions and language is infinitely rephrasable.
- Others argue for layered defenses: structured inputs with roles/priority, separate “auditor” models, and analogies to CPU protections that, while imperfect, dramatically reduce risk.
- There is disagreement on whether a hard separation between “data” and “instructions” is even possible for broad reasoning systems.
Containment, Sandboxing, and Local Tools
- Strong support for local, containerized or micro‑VM style execution with strict filesystem mounts, read‑only inputs, and constrained network access.
- Some question how much containers help if tools still need broad file/network access to be useful.
- Ideas include WASI-based sandboxes, proxies that mediate all external calls, and domain whitelists.
Vendor Response and Disclosure Handling
- A representative from the affected vendor acknowledges the issue and says they disabled a key capability (Apps Script generation) while re‑evaluating sandboxing.
- Many criticize the initial non-response to email disclosure and worry that user protection depended on public shaming.
- Some suggest the security reporting pipeline is overwhelmed or poorly designed, undermining trust.
Enterprise Data Exfiltration Concerns
- Exfiltration is cited as a major blocker to using agents in sensitive environments, even on-prem.
- Proposals: on-prem local models, anonymized/obfuscated datasets, and agent proxies enforcing authz and monitoring for exfiltration or prompt injection.
- Trade-off noted: strong network/egress controls often neuter the agent’s usefulness.
General Attitudes Toward AI Security
- Many see “move fast and break things” culture persisting, with trillion‑dollar incentives overriding thorough safety vetting.
- Historical analogies are drawn to macro viruses and insecure early operating systems; some expect a similar long, painful learning curve before defaults become safe.