Topic starter
24/09/2026 1:27 pm
TL;DR: .env files store secrets as plaintext on disk, making them easy to leak through git, Slack, and filesystem reads, while AI coding agents now expand that exposure by reading project files automatically, according to Akeyless. The practical endpoint is runtime injection of short-lived credentials, because static secrets on disk no longer match how developers and agents work.
NHIMG editorial — based on content published by Akeyless: why .env files are failing as secret storage in AI workflows
By the numbers:
- Only 5.7% of organisations have full visibility into their service accounts.
- 71% of NHIs are not rotated within recommended time frames, increasing the risk of compromise over time.
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
Questions worth separating out
Q: How should security teams reduce the risk of developer secrets stored in local .env files?
A: Security teams should make the safer path the easiest path.
Q: Why do .env files create a bigger risk when AI coding agents are in the workflow?
A: Because AI coding agents read project files automatically, a plaintext secret can move from a local file into a model’s context, generated output, or chat history without any deliberate sharing.
Q: When should organisations replace .env files with runtime injection?
A: They should do it as soon as developers are using AI coding agents that can read workspace files.
Practitioner guidance
- Classify .env contents by sensitivity Split non-sensitive configuration from real credentials, API keys, database passwords, and tokens.
- Remove plaintext secrets from developer workspaces Prevent secrets from sitting in directories that AI coding agents, backup jobs, or shared tools can read automatically.
- Adopt runtime injection for production access Inject short-lived secrets at execution time for applications, CI/CD jobs, and ephemeral workloads so the credential does not exist as a durable file on disk.
What's in the full article
Akeyless's full article covers the operational detail this post intentionally leaves for the source:
- A practical comparison of plain .env handling, encrypted file tools, and secrets managers for different development stages
- Examples of how runtime injection works across local development, CI/CD, containers, and ephemeral workloads
- Guidance on where environment variables still help and where they stop being a safe boundary
- Operational examples of keeping AI coding agents away from raw secret values while still supporting developer workflows
👉 Read Akeyless's analysis of why .env files are failing as secret storage →
.env files, AI coding tools, and the secret storage gap?
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24/09/2026 1:27 pm
Plaintext credential storage is no longer just a developer hygiene issue, it is a lifecycle failure. When a secret lives in a .env file, it is outside the normal controls that identity teams rely on for inventory, rotation, revocation, and audit. The practical conclusion is that credentials stored on disk should be treated as unmanaged NHIs, not as harmless configuration.
A few things that frame the scale:
- 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools, according to the Ultimate Guide to NHIs.
- 79% of organisations have experienced secrets leaks, with 77% of these incidents resulting in tangible damage, showing that exposed credentials are already a business problem, not just a hygiene issue.
A question worth separating out:
A: Environment variables are a deployment convenience, while a secret manager is a control designed to protect sensitive values. Variables can be exposed through configuration access, logs, process inspection, or accidental sharing. A secret manager centralises storage, supports tighter access controls, and reduces secret sprawl across functions and environments. For serverless workloads, that difference materially changes the blast radius of a compromise.
👉 Read our full editorial: Why .env files are failing as secret storage in AI workflows
