Email Header Injection: Turning Contact Forms into Spam Cannons 📧

https://instatunnel.my/blog/email-header-injection-turning-contact-forms-into-spam-cannons

https://redd.it/1oqlody
@r_devops

Azure pipeline limitations DockerCompose@1

Folks, I was trying to build image for a specific service of my compose file but I unable to do with pipeline. I found only below from azure doc, why it is there for only run? not for build?

serviceName \- Service Name
string. Required when action = Run a specific service.

https://redd.it/1oqniv9
@r_devops

How do you track if code quality is actually improving?

We’ve been fixing a lot of tech debt but it’s hard to tell if things are getting better. We use a few linters, but there’s no clear trend line or score.
Would love a way to visualize progress over time, not just see today’s issues.

https://redd.it/1oqqcsv
@r_devops

How to Post CodeQL Analysis Results (High/Critical Counts + Details) as a Comment on a GitHub Pull Request?


I'm working with a custom-built CodeQL GitHub Actions workflow, and I want to automatically push the analysis results directly into a comment on the pull request. Specifically, I'd like to include things like the count of high and critical severity issues, along with some details about them (e.g., denoscriptions, locations, etc.).

I need them visible in the PR for easier review. Has anyone done something similar? Maybe by parsing the SARIF file and using the GitHub API to post a comment?

Any step-by-step guidance, workflow YAML snippets, or recommended actions/tools would be awesome. Thanks in advance!

https://redd.it/1oqshfj
@r_devops

Machine learning research internship

For my career and for future internships as a CS/math student at a top 20 University, how competitive is a machine learning research internship at a good European University? I have an opportunity to spend 3 months at this University (different continent) and work on implementing cutting edge information retrieval and NLP models/methods. Would this experience make me competitive for future internships or is it pretty standard? I am just trying to get this jist of its significance seeing that I’ll be spending a substantial amount of time there next year.

https://redd.it/1oqtbmo
@r_devops

Do you use containers for local development or still stick to VMs?

I’ve been moving my workflow toward Docker and Podman for local dev, and it’s been great lightweight, fast, and easy to replicate environments.
But I’ve seen people say VMs are still better for full OS-level isolation and reproducibility.
If you’re doing Linux development, what’s your current setup containers, VMs, or bare metal?

https://redd.it/1oqw1cq
@r_devops

Cutting down on TAC tickets

Looking for opinions on a topic of TAC support.

Having been on the both sides of the issue (both as tech support and admin) - I am a bit aware know how slow and sometimes unprofessional it can get.

Not really because TAC or admins are not knowledgeable - there is not enough time to be knowledgeable due to repetitiveness and constantly growing amount of information that has to be expedited to customers/users.

Sprinkle into it the fact, that even internally - you don’t have enough info. Or it’s structured in a way that makes you question how this all been holding up in the first place.

Average engineer gets 10+ calls per day +a certain amount of tickets that are more or less proportionate to the amount of calls. Some of these calls are expectingly easy, some can take a crazy amount of time to figure out.

And sometimes you have to lab the setup, look for similar issues while having another customer waiting for you to reply. It literally takes days due to simple tasks just repeating.

So I started looking for a way to cut down on this repetitive bureaucratic idiocy and cut down on resolving tac tickets using AI.

For two reasons:

1. In critical scenario it’s almost impossible to get the right guy on the phone. I remember getting a call once from some sort of school or other educational facility - their certificate authentication was failing for everyone and system administrator was on vacation. As L1 - I was hella lucky to be familiar with setup (ms ca -> fortiauth as sub-ca -> 802.11x with certs).

Imagine some L1 who just got out of uni and gets on a call like that. No amount of theoretical knowledge will prepare them for the pressure of 10 people staring at their avatar in GoToMeeting, being at a complete loss and thinking your are their only chance to make it work. That leads us to reason 2.

2. It will free up time for engineers to actually learn the product. Enormous amounts of best practices depends on some person just knowing a certain combination of toggles which is not in the docs.

That would free up their time to get to know the product and be actual tech support. I might be missing a certain angle here so please feel free to critique.

That’s is how i came with question - how can an AI solve all that for folks who are in similar context?

Not like - “do stuff for me and we will see”. Use it for actual assistance - ask it questions, help inspect devices, configure them. So human would still be the one making decisions but AI doing all the grunt work?

I’m saying it because I refuse to believe that simple log analysis should take days to complete.

So what’s your experience guys? How long on average it takes to deal with TAC? Is it different per product/vendor?

Share your thoughts, let’s find a consensus!

https://redd.it/1or13mz
@r_devops

I built sbsh to keep my team’s terminal environments reproducible across Kubernetes, Terraform, and CI setups

I have been working on a small open-source tool called sbsh that makes terminal sessions persistent, reproducible, and shareable.

Repo: github.com/eminwux/sbsh

It started from a simple pain point: every engineer on a team ends up with slightly different local setups, environment variables, and shell aliases for things like Kubernetes clusters or Terraform workspaces.

With sbsh, you can define those environments declaratively in YAML, including variables, working directory, hooks, prompt color, and safeguards.

Then anyone can run the same terminal session safely and identically. No more “works on my laptop” when running terraform plan or kubectl apply.

Here is an example for Kubernetes: docs/profiles/k8s-default.yaml

apiVersion: sbsh/v1beta1
kind: TerminalProfile
metadata:
name: k8s-default
spec:
runTarget: local
restartPolicy: restart-on-error
shell:
cwd: "~/projects"
cmd: /bin/bash
cmdArgs:
env:
KUBECONF: "$HOME/.kube/config"
KUBECONTEXT: default
KUBENAMESPACE: default
HISTSIZE: "5000"
prompt: '"[\e1;31m\sbsh($SBSHTERMPROFILE/$SBSHTERMID) [\e1;32m\\u@\h[\e0m\:\w\$ "'
stages:
onInit:
- noscript: kubectl config use-context $KUBECONTEXT
- noscript: kubectl config get-contexts
postAttach:
- noscript: kubectl get ns
- noscript: kubectl -n $KUBENAMESPACE get pods

Here's a brief demo:

sbsh - kubernetes profile demo

You can also define profiles for Terraform, Docker, or even attach directly to Kubernetes pods.

Terminal sessions can be detached, reattached, listed, and logged, similar to tmux but focused on reproducible DevOps environments instead of window layouts.

Profile examples: docs/profiles

I would really appreciate any feedback, especially from people who manage multiple clusters or Terraform workspaces.

I am genuinely looking for feedback from people who deal with this kind of setup, and any thoughts or suggestions would be very much appreciated.

https://redd.it/1or36aw
@r_devops

If teams moved to “apps not VMs” for ML dev, what might actually change for ops?

Exploring a potential shift in how ML development environments are managed. Instead of giving each engineer a full VM or desktop, the idea is that every GUI tool (Jupyter, VS Code, labeling apps) would run as its own container and stream directly to the browser. No desktops, no VDI layer. Compute would be pooled, golden images would define standard environments, and the model would stay cloud-agnostic across Kubernetes clusters.

A few things I am trying to anticipate:

* Would environment drift and “works on my machine” actually decrease once each tool runs in isolation?
* Where might operational toil move next - image lifecycle management, stateful storage, or session orchestration?
* What policies would make sense to control costs, such as idle timeouts, per-user quotas, or scheduled teardown of inactive sessions?
* What metrics would be worth instrumenting on day one - cold start latency, cost per active user, GPU-hour distribution, or utilization of pooled nodes?
* If this model scales, what parts of CI/CD or access control might need to evolve?

Not pitching anything. Just thinking ahead about how this kind of setup could reshape the DevOps workflow in real teams.

https://redd.it/1or6lal
@r_devops

Retraining prompt injection classifiers for every new jailbreak is impossible

Our team is burning out retraining models every time a new jailbreak drops. We went from monthly retrains to weekly, now it's almost daily with all the creative bypasses hitting production. The eval pipeline alone takes 6 hours, then there's data labeling, hyperparameter tuning, and deployment testing.

Anyone found a better approach? We've tried ensemble methods and rule-based fallbacks but coverage gaps keep appearing. Thinking about switching to more dynamic detection but worried about latency.

https://redd.it/1orc5kb
@r_devops

A playlist on docker which will make your skilled enough to make your own container

I have created a docker internals playlist of 3 videos.

In the first video you will learn core concepts: like internals of docker, binaries, filesystems, what’s inside an image ? , what’s not inside an image ?, how image is executed in a separate environment in a host, linux namespaces and cgroups.

In the second one i have provided a walkthrough video where you can see and learn how you can implement your own custom container from scratch, a git link for code is also in the denoscription.

In the third and last video there are answers of some questions and some topics like mount, etc skipped in video 1 for not making it more complex for newcomers.

After this learning experience you will be able to understand and fix production level issues by thinking in terms of first principles because you will know docker is just linux managed to run separate binaries.
I was also able to understand and develop interest in docker internals after handling and deep diving into many of production issues in Kubernetes clusters. For a good backend engineer these learnings are must.

Docker INTERNALS
https://www.youtube.com/playlist?list=PLyAwYymvxZNhuiZ7F_BCjZbWvmDBtVGXa

https://redd.it/1orelme
@r_devops

Unicode Normalization Attacks: When "admin" ≠ "admin" 🔤

https://instatunnel.my/blog/unicode-normalization-attacks-when-admin-admin

https://redd.it/1orfljl
@r_devops

OpenSource work recommendations to get into devops?

Have 5YOE mostly as backend developer, with 3 years IAM team at big company (interviewers tend to ask mostly about this).

Recently got AWS Solutions Architect Professional which was super hard, though IAM was quite a bit easier since I've seen quite a few of the architectures while studying that portion of the exam. Before I got the SAP, I had SAA and many interviews I got were CI/CD roles which I bombed. When I got the SAP, I got a handful of interviews right away, none of which were related to AWS.

I don't really want to get the AWS DevOps Pro cert as I heard they use Cloudformation which most companies don't use. Also don't want to have to renew another cert in 3 years (SAP was the only one I wanted).

Anyways, I'm currently doing some open source work for aws-terraform-modules to get familiarized with IaC. Suprisingly, tf seems super simple. Maybe it's the act of deploying resources with no errors which is the key.

So basically, am I on the right track? Should I learn Ansible? Swagger? etc.
Did a few personal projects on Github, but I doubt that will wow employers unless I grind out something original.

Here's my resume btw: https://imgur.com/a/Iy2QNv6

https://redd.it/1org8l4
@r_devops

Offline postman alternative without any account.

Postman was great with rich features like api flows till it went cloud only which is a deal breaker for me.

Since then I was looking for offline only api client with complex testing support like api flows through drag and drop ui, noscripting.

Found HawkClient that works offline without any account, support api flows through drag and drop ui, noscripting, collection runner.

curious to know has any one else tried hawkclient or any other tool that meets the requirement.

https://redd.it/1ori0ld
@r_devops

doubts of mine ?

me facing problem while learning something like :
"from where should i have to learn ?"
"how much i have to learn ?"
etc ...
all these questions come to my mind while learning.
if you face these problem let me know how you handle these with an example.

https://redd.it/1ormrzd
@r_devops

Token Agent – Config-driven token fetcher/rotator

Hello!

I'm working on a simple Token Agent service designed to manage token fetching, caching/invalidation, and propagation via a simple YAML config.



>metadata API → token exchange service → http | file | uds



It was originally designed for cloud VM.

It can retrieve data from metadata APIs or internal HTTP services, and then serve tokens via files, sockets, or HTTP endpoints.

Resilience and Observability included.

Use cases generic:

\- Keep workload tokens in sync without custom noscripts

\- Rotate tokens automatically with retry/backoff

\- Define everything declaratively (no hardcoded logic)

Use cases for me:

\- Passing tokens to vector.dev via files

\- Token source for other services on vm via http

Repo: github.com/AleksandrNi/token-agent

Would love feedback from folks managing service credentials or secure automation.

Thanks!

https://redd.it/1ormmne
@r_devops

Do companies hire DevOps freshers?

Hey everyone

I’ve been learning DevOps tools like Docker, CI/CD, Kubernetes, Terraform, and cloud basics. I also have some experience with backend development using Node.js.

But I’m confused — do companies actually hire DevOps freshers, or do I need to first work as a backend developer (or some other role) and then switch to DevOps after getting experience?

If anyone here started their career directly in DevOps, I’d love to hear how you did it — was it through internships, projects, certifications, or something else?

Any advice would be really helpful

https://redd.it/1oroiqp
@r_devops

Kubernetes operator for declarative IDP management

Since 1 year, I've been developing a Kubernetes Operator for Kanidm identity provider.

From the release notes:
Kaniop is now available as an official release! After extensive beta cycles, this marks our first supported version for real-world use.

Key capabilities include:

Identity Resources: Declaratively manage persons, groups, OAuth2 clients, and service accounts
GitOps Ready: Full integration with Git-based workflows for infrastructure-as-code
Kubernetes Native: Built using Custom Resources and standard Kubernetes patterns
Production Ready: Comprehensive testing, monitoring, and observability features

If this sounds interesting to you, I’d really appreciate your thoughts or feedback — and contributions are always welcome.

Links:
repository: https://github.com/pando85/kaniop/
website: https://pando85.github.io/

https://redd.it/1orq23c
@r_devops

VSCode multiple ssh tunnels

Hi All. Hoping this is a good place for this question.
I currently work heavily in devcontainer based environments often using GitHub Codespace. Our local systems are heavily locked down so even getting simple cli tools installed is a pain. A platform we use is setting up the ability to run code through the remote ssh extension capabilities. Ideally allowing us to use VSCode while leveraging the remote execution environment.
However it seems like I can't use that while connected to a codespace since uses the tunnel. I looked into using a local docker image on wsl but again that uses the tunnel.
Anything you can think of to keep the devcontainer backed environment but then still be able to tunnel to the execution environment?

https://redd.it/1orqufh
@r_devops

I created a cool uhmegle extension

I created this useful extension for Uhmegle called ChillTools. It shows you the other person’s IP address and approximate location while you chat. It also keeps a log of the last 30 people you’ve talked to, saving their IP and a screenshot so you can look back later. it have also a country filter a block people system and custom personaliziation with ccs The extension is completely free, open source, and transparent no hidden code or anything suspicious. You can download it from here .gg/FBsPkXDche. If you use Uhmegle often, this might be helpful

https://redd.it/1ortiuo
@r_devops

Created a minimal pipeline with github connection , codebuild. Succeeds when created but no subsequent pushes create builds/triggers. No event bridge rules created

Here is the cloudformation

Removed some parts as it's too long.

But the core logic is to trigger a build on a repo/branch using am existing connection.

Will this create event bridge rules?
None have been created .
Or do I need to add the event triggers for any push to this repo/branch.
Llm says they will be created automatic and there is some issues creating them. Thank you in advance.


AWSTemplateFormatVersion: '2010-09-09'
Denoscription: Minimal CodePipeline with CodeStar Connection (GitHub) Trigger & CodeBuild

Parameters:
PipelineName:
Type: String
Default: TestCodeStarPipeline

GitHubOwner:
Type: String
Denoscription: GitHub user or org name (e.g. octocat)
GitHubRepo:
Type: String
Denoscription: GitHub repository name (e.g. Hello-World)
GitHubBranch:
Type: String
Default: main
Denoscription: Branch to track (e.g. main)

CodeStarConnectionArn:
Type: String
Denoscription: ARN of your AWS CodeStar connection to GitHub

Resources:
ArtifactBucket:
Type: AWS::S3::Bucket
Properties:
VersioningConfiguration:
Status: Enabled

PipelineRole:
Type: AWS::IAM::Role
Properties:
AssumeRolePolicyDocument:
Statement:
- Effect: Allow
Principal: { Service: codepipeline.amazonaws.com }
Action: sts:AssumeRole
Path: /
Policies:
- PolicyName: ArtifactS3Access
PolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Action:
- s3:GetObject
- s3:PutObject
- s3:ListBucket
Resource:
- !Sub '${ArtifactBucket.Arn}'
- !Sub '${ArtifactBucket.Arn}/*'
- Effect: Allow
Action: codestar-connections:UseConnection
Resource: !Ref CodeStarConnectionArn
- Effect: Allow
Action:
- codebuild:StartBuild
- codebuild:BatchGetBuilds
Resource: '*'

BuildRole:
Type: AWS::IAM::Role
Properties:
AssumeRolePolicyDocument:
Statement:
- Effect: Allow
Principal: { Service: codebuild.amazonaws.com }
Action: sts:AssumeRole
Path: /
ManagedPolicyArns:
- arn:aws:iam::aws:policy/AmazonS3ReadOnlyAccess
- arn:aws:iam::aws:policy/CloudWatchLogsFullAccess

CodeBuildProject:
Type: AWS::CodeBuild::Project
Properties:
Name: !Sub '${PipelineName}-build'
ServiceRole: !GetAtt BuildRole.Arn
Artifacts:
Type: CODEPIPELINE
Environment:
ComputeType: BUILD_GENERAL1_SMALL
Image: aws/codebuild/amazonlinux2-x86_64-standard:5.0
Type: LINUX_CONTAINER
Source:
Type: CODEPIPELINE
BuildSpec: |
version: 0.2
phases:
build:
commands:
- echo "Hello World from CodeBuild"
artifacts:
files:
- '**/*'

Pipeline:
Type: AWS::CodePipeline::Pipeline
Properties:
Name: !Ref PipelineName
RoleArn: !GetAtt PipelineRole.Arn
ArtifactStore:
Type: S3
Location: !Ref ArtifactBucket
Stages:
- Name: Source
Actions:
- Name: Source
ActionTypeId:
Category: Source
Owner: AWS
Provider: CodeStarSourceConnection
Version: '1'
Configuration:
ConnectionArn: !Ref CodeStarConnectionArn
FullRepositoryId: !Sub "${GitHubOwner}/${GitHubRepo}"
BranchName: !Ref GitHubBranch
OutputArtifactFormat: CODE_ZIP
OutputArtifacts:
- Name: SourceArtifact
RunOrder: 1
- Name: Build