•1 min read•from Data Science
How does your team handle the security issues of coding agents on real data?
Been thinking about this a lot lately. We use coding agents daily on real datasets.
Two things I read recently that made me uncomfortable:
- Prompt injection : basically the agent read some website to files on Internet, then some hidden instructions it'll just execute and can exfiltrate data to external server?
- Slopsquatting: LLMs hallucinate package names that don't exist. Attackers pre-register the most-hallucinated names on PyPI with malware.
This is a few I can think of but it makes me wonder how other teams manage it? Do you believe those are real risks or some security researchers fantasy?
[link] [comments]
Want to read more?
Check out the full article on the original site
Tagged with
#real-time data collaboration
#real-time collaboration
#big data management in spreadsheets
#generative AI for data analysis
#conversational data analysis
#rows.com
#Excel alternatives for data analysis
#intelligent data visualization
#data visualization tools
#enterprise data management
#big data performance
#data analysis tools
#data cleaning solutions
#financial modeling with spreadsheets
#prompt injection
#slopsquatting
#coding agents
#security issues
#data security
#hallucination