2026-01-16 06:50:54
Apache DolphinScheduler's alerting system, powered by a sophisticated SPI plugin architecture, safeguards data workflows. Among these, email notification via the SMTP protocol serves as a vital link for timely information delivery.
\ When the status of a workflow or task changes—whether it completes successfully, fails, or times out—the alert system responds instantly, automatically triggering an email notification to ensure relevant personnel are informed immediately.
\ Notably, the system supports a wide range of alerting methods, including Email, DingTalk, WeChat Work, Scripts, SMS, Feishu, Slack, PagerDuty, WebexTeams, Telegram, HTTP, and Alibaba Cloud Voice, fully meeting the diverse needs of different scenarios and users.
\ This article focuses deeply on Email alerts, presenting a comprehensive guide to setup and usage. It covers everything from creating an Email alert instance and fine-tuning SMTP parameters to building alert groups and linking them with workflows. Additionally, it provides an in-depth analysis of the mail delivery mechanism, shares practical best practices, and offers troubleshooting methods for common issues to help you master and efficiently use the Email alert feature.
The Email alert system consists of the following core components:
Log in to the DolphinScheduler Web UI.
Navigate to "Security" -> "Alert Instance Management."
Click "Create Alert Instance."
Select "Email" as the alert plugin type.
The Email alert instance requires the following key parameters:
| Parameter | Description | Required | Example | |----|----|----|----| | server | SMTP server address | Yes | smtp.gmail.com | | port | SMTP port | Yes | 587 | | sender | Sender email address | Yes | [email protected] | | user | SMTP auth username | Yes | [email protected] | | password | SMTP auth password | Yes | yourpassword | | enableSmtpAuth | Enable SMTP authentication | Yes | true | | enableTls | Enable TLS encryption | No | true | | enableSsl | Enable SSL encryption | No | false | | receivers | Recipient list | Yes | [email protected] |
An alert group is a collection of alert instances used to manage multiple alert channels uniformly:
Associate the alert group with a workflow definition:
The core logic for sending emails is implemented in the MailSender class:
// Main steps for sending email
1. Create an SMTP session
2. Configure mail server parameters
3. Construct email content
4. Send the email
5. Handle the delivery results
\ The system supports HTML email templates for better readability.
Email alerts are automatically triggered in the following scenarios:
SQL tasks support sending query results via email; the following parameters need to be configured:
sendEmail: Enable email notification.title: Email subject.groupId: Alert group ID.DolphinScheduler’s Email alert feature provides a complete workflow monitoring and notification mechanism. By properly configuring alert instances, groups, and workflow associations, you can ensure timely access to system status information. It is recommended to combine this with other alert channels (like DingTalk or WeChat) in production to build a robust monitoring system.
This document is based on DolphinScheduler’s SPI plugin architecture. Email alerting is a built-in plugin. The system supports custom extensions; for development, please refer to the GitHub Alert SPI documentation at: docs/docs/en/contribute/backend/spi/alert.md.
2026-01-16 05:46:37
I have spent some time last year implementing Cloudflare Tunnels on my Home Assistant and my Synology NAS. On Mastodon, I had not one but two commenters advertising for Tailscale:
https://mastodon.top/@frankel/115639107167365460?embedable=true
I decided to give it a try and migrate my servers and devices to Tailscale. In this post, I want to describe how I did. Thanks to Heiko Does and Higgins for prompting me to look further!
A Zero Trust identity-based connectivity platform that replaces your legacy VPN, SASE, and PAM and connects remote teams, multi-cloud environments, CI/CD pipelines, Edge & IoT devices, and AI workloads.
-- Tailscale
\ In other words, Tailscale allows creating a mesh VPN that your devices can connect to. Devices can then communicate with each other inside the network, isolated from the rest of the world. With my current Cloudflare Zero-trust setup, the problem is that my user devices aren't on the network. Hence, I need to provide public endpoints for my services, which come with privacy and security issues.
\ Tailscale solves them instantly. My user devices on the same isolated network remove the need for public endpoints. At this point, I knew I had to make the move.
The user experience of onboarding on Tailscale is amazing. You chose among a handful of identity providers, and you're on. Tailscale delegates all authentication to the chosen +++IdP+++. Choose wisely: you can't bind your account to multiple IdPs to have a fallback.
\ By default, Tailscale onboards you on a 14-day free Enterprise trial plan. You can change to a personal free plan to avoid building on features that aren't necessary. The plan offers three different users and 100 devices. It's more than I need.
I added my servers and devices to the mesh by installing Taiscale on each of them, then authenticating with the IdP. Here are the supported OS:
\ I did use the web-based IdP authentication because my servers provide such an interface. If yours don't, or if your fleet needs solid DevOps practices, you can generate a ready-made script with a dedicated enrolment key. I think there's even an API for this.
\ You might have noticed I used two different words: server and device. Devices are tied to a physical person's identity; servers aren't. Once authenticated, you can move the server to a tag.
\
Tags are essentially service accounts, but with more flexibility⎯you can assign multiple tags to a device to account for multiple purposes.
\ It makes the semantics clearer. I did, even if I'm not sure about the benefits in my single-user setup.
I migrated from Cloudflare Tunnel and public endpoints to Tailscale. It netted me gains and losses. Here is what I found out.
\
First and foremost, since I'm running my own mesh, I don't need to have a public endpoint. Without an endpoint, I need neither a subdomain nor a TLS certificate that leaks my server's home IP. Tailscale provides a dedicated subdomain of ts.net. You can choose between a random string (I assume it's your network ID) or a combination of adjective plus noun. Fun fact: the latter offers 3 choices, but you can "re-roll" until you get something that suits your fancy.
\ My previous setup with Cloudflare Tunnels worked with HTTP endpoints. Thus, I had no remote SSH access. Now, I can access my servers from my computer remotely, wherever I want. I never needed it before, but it can be very useful during a long trip abroad, when your home infrastructure starts misbehaving.
\ Likewise, I didn't create dedicated endpoints to synchronize my pictures and my music on the Synology. I only synchronized through the IP on the internal network. As soon as I connect to Tailscale on my devices, I get both. Given that the iPad version of DS Audio doesn't offer caching to listen offline, that's a great benefit.
\ Tailscale offers a feature called MagicDNS. It allows referencing servers and devices by their name, optionally suffixed by the Tailscale domain name. All in all, you can access them in several ways:
| Type | Example |
|----|----|
| IP v4 | 100.98.98.68 |
| IP v6 | fd7a:115c:a1e0::3701:6261 |
| Fully qualified name | nas.pTsDVj8tCL11XNTRL.ts.net |
| Simple name | nas |
\ And finally, I could remove all the port forwarding rules on my home router.
\ All the above are net gains, but there are some losses too. Because I let go of subdomains, I need to remember ports when multiple apps are available on the same host. Tailscale offers services to alias a port, but the Tailscale version that comes with the Synology plugin doesn't.
\ By default, Tailscale doesn't provide TLS over internal servers. It does allow generating certificates, though. I'm too lazy to configure them right now, because the idea of a private mesh should protect from man-in-the-middle attacks. In addition, if Tailscale wants to eavesdrop on the traffic, it could, since Tailscale generates certificates anyway.
\ The last hurdle is network access from devices that Tailscale doesn't support, e.g., smart watches. In theory, I would be able to access my Home Assistant from my Garmin watch via the relevant app. I have installed it, but never used it. With neither a public endpoint nor specialized software, I can't use it anymore. For this specific use case, Tailscale provides Subnets.
\ I'll need to check into the features later.
Migrating to Tailscale was a leap of faith, but I'm very happy I did it. My setup has improved a lot, both in terms of privacy and security. It is also much simpler regarding my requirements. I encourage you to have a look.
\ To go further:
Originally published at A Java Geek on January 11th, 2026
\
2026-01-16 05:45:00
The AI History Timeline explores what brought us to the AI boom, and was made in collaboration with Claude, Gemini, and ChatGPT, i.e. the best currently available AI deep researchers, as part of the launch of HackerNoon.ai, our approach to blogging through the AI boom. We will update the AI development timeline periodically, but publish the initial 251 most important events we curated.
2026-01-16 04:54:41
New York, United States, January 15th, 2026/CyberNewsWire/--BreachLock, a global leader in offensive security, today announced that its Adversarial Exposure Validation (AEV) solution now supports autonomous red teaming at the application layer, expanding beyond its initial network-layer capabilities introduced in early 2025.
BreachLock AEV’s generative AI-powered autonomous red teaming engine can now emulate real-world attacker behavior at the application layer, capturing how adversaries think, pivot, and chain exploits. AEV continuously validates exploitable weaknesses in applications, including cross-site scripting (XSS), code injection flaws, OWASP Top 10 vulnerabilities, business logic flaws, and complex exploit paths.
BreachLock AEV goes beyond simply identifying theoretical risks and validates their real-world exploitability and business impact. These deep contextual insights help enterprise security teams scale their coverage and reduce critical risks faster with a sharper focus on remediating the validated risks that pose the greatest threat to their organization.
“Security teams don’t need more tools—they need better outcomes,” Seemant Sehgal, Founder & CEO of BreachLock, said. “With agentic autonomous penetration testing for web applications, we’re pushing the boundaries of what offensive security can do by continuously thinking, adapting, and validating risk the way real attackers do. This is a fundamental shift in how organizations measure and improve their security posture,” he added.
BreachLock AEV includes an interactive, real-time attack path visualization feature, allowing users to see where their defenses pass and fail across the attack chain. Users can also download detailed, MITRE ATT&CK-aligned PDF reports directly from the BreachLock Unified Platform, making it easier to communicate findings, prioritize remediation, and demonstrate compliance.
To learn more about BreachLock AEV, users can visit BreachLock.com.
BreachLock is a global leader in offensive security, delivering scalable and continuous security testing. Trusted by global enterprises, BreachLock provides human-led and AI-powered Attack Surface Management, Penetration Testing as a Service (PTaaS), Red Teaming, and Adversarial Exposure Validation (AEV) solutions that help security teams stay ahead of adversaries.
With a mission to make proactive security the new standard, BreachLock is shaping the future of cybersecurity through automation, data-driven intelligence, and expert-driven execution.
Marketing Communications Manager
Megan Charrois
BreachLock
:::tip This story was published as a press release by Cybernewswire under HackerNoon’s Business Blogging Program. Do Your Own Research before making any financial decision.
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2026-01-16 04:44:52
McLean, Virginia, United States, January 15th, 2026/CyberNewsWire/--A new Top 10 Cybersecurity Innovators profile by AppGuard has been released, spotlighting growing concerns over AI-enhanced malware. AI makes malware even more difficult to detect. Worse, they use AI to assess, adapt, and move faster than any cyber stack can keep up.
The report advocates for a fundamental change in approach, highlighting the limitations of reactive security measures. Rather than constantly adding or changing detection layers of cyber stacks, the profile emphasizes the importance of reducing endpoint attack surface—a perspective that challenges conventional industry practices.
CEO Fatih Comlekoglu mentions that “You can’t keep trying to tell good from bad among infinite possibilities. Not even the most magical AI can parse infinity.”
The industry is trapped in a futile chase, piling on detection tools and adding AI enhancements that still fail to close the foundational gap. In fact, enterprises now face an overwhelming flood of alerts, with many organizations reportedly beginning to limit the amount of data they ingest simply because they can no longer keep up.
Once remote control is established on an endpoint, adversarial AI reportedly adjusts the malicious process's activities in real-time to evade detection and adapt to the environment. This dramatically shortens the time defenders have to respond and exacerbates flaws in detection-based security that depend on human approvals or interventions.
AI cannot parse infinity; AI can only parse what it can, faster. Instead of joining the futile chase, “default-deny” or Zero Trust enforced within endpoints shrinks the attack surface. By restricting what can run and what the running can do, attacks run into walls, regardless of disguise or AI acceleration. The concept is akin to football: shrink the adversary’s "playing field" as well as its “playbook”.
Many controls-based layers can theoretically shrink the attack surface to some degree but few do so practically, thoroughly, and without considerable friction. AppGuard does this with 10 to 100 times fewer policy rules than alternatives.
Even better, it uniquely auto-adapts to endpoint changes and malware technique variations. Fewer rules and fewer rules changes equate to easier operations and greater efficacy against malware, even AI-guided malware.
While AI is increasingly promoted as a breakthrough in cybersecurity, it remains a form of advanced pattern matching—subject to the same limitations as traditional detection methods. AppGuard affirms that it does not rely on AI for malware detection.
Instead, the company sees AI enhancing its controls-based approach to endpoint protection. This includes improving attack surface management, minimizing disruption to legitimate workflows, and providing clearer visibility into policy enforcement and blocked events.
Following recognition in the recent cybersecurity innovators profile, AppGuard has reopened its Insider Release program. The initiative seeks experienced endpoint security professionals—particularly those at MSSPs and MSPs managing multiple client environments—to provide hands-on feedback on AppGuard’s upcoming reengineered endpoint protection platform.
Selected participants will have early access to deploy the newly architected lightweight agent in combination with AppGuard’s new cloud-based management console.
Seats are limited and reserved for qualified teams with proven operational experience. Readers apply here. Selected participants receive: early access to the new agent and cloud console and direct influence on final features and roadmap priorities.
Resources
Adding AppGuard to ANY cyber stack to stop what other layers miss entirely or detect too late: zero-days, ransomware, process injection, credential theft, info-stealers, living-off-the-land techniques.
AppGuard’s effectiveness is not theoretical. It has been proven repeatedly in the field for very large organizations to very small. For example, one of the world’s largest airlines, managing more than 40,000 endpoints, had been plagued by weekly malware incidents despite deploying multiple high-end cybersecurity solutions.
After implementing AppGuard in 2019, the organization has experienced no successful malware breaches—a testament to the product’s real-world impact. Small businesses appreciate its easy deployment and the resulting end-user productivity.
AppGuard is the real-time, controls-based endpoint protection layer that stops what detection tools miss entirely or detect too late. It extends Zero Trust principles into the endpoint itself—down to the computing process—filling a critical gap where traditional Zero Trust models treat the endpoint as a black box.
Adding it to any cyber stack delivers enterprise-grade protection with dramatically fewer rules, far less tuning, and far less operational overhead. AppGuard is ideal for both smaller organizations and large enterprises tired of spending fortunes on porous, alert-heavy defenses that still fail.
Marketing
Eirik Iverson
AppGuard Inc
:::tip This story was published as a press release by Cybernewswire under HackerNoon’s Business Blogging Program. Do Your Own Research before making any financial decision.
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2026-01-16 04:09:41
In crypto markets, prices rarely wait for utility to go live before they begin to reflect it. Traders often push valuations higher as utility approaches.
This happens because anticipation itself can drive capital inflows. Assets tied to lending, borrowing, or real revenue models often see price movement before users arrive on-chain. One new crypto is entering that key anticipation phase, and its recent 3x price surge is showing how markets price in expected activity before it begins.
Why do utility expectations move prices early? Protocols that generate real cash flows have value drivers that go beyond narrative. In lending systems, users deposit assets and borrowers pay interest.
These flows create measurable revenue once markets are live. When a project approaches that moment, price can reprice toward where usage may settle once real activity begins.
The token behind this story is Mutuum Finance (MUTM). Mutuum Finance is a new crypto project building a decentralized lending and borrowing protocol on Ethereum. The goal is to support markets where users supply liquidity and earn yield while others borrow against collateral under set rules.
The utility here is simple: deposits earn yield from borrowing activity, and borrowers access liquidity without middlemen. Protocol fees and interest create revenue potential that did not exist before utility activation.
This context matters because price appreciation can occur before public usage hits the network. Traders look at roadmaps, testnets, and audit reports and price those events into crypto prices ahead of launch. With Mutuum Finance close to its V1 protocol launch, expectations are shifting from idea to execution. This is ideal timing for a reprice if on-chain activity begins soon.
Mutuum Finance opened its token offering early in 2025 at an initial price of $0.01. Pricing then advanced in defined steps as each allocation stage filled. The sale is now in presale Phase 7, where MUTM is sold at $0.04, reflecting an increase of roughly 3x from the opening stage.
The distribution has attracted broad participation, with more than 18,800 wallets holding MUTM. The presale has raised over $19.7 million to date. From the full 4 billion supply, 45.5% is allocated for early distribution, and more than 825 million tokens have already been sold.
This pricing progression is important. As the next utility moment approaches, the remaining supply at lower prices shrinks. That means fewer opportunities for late buyers to enter before utility arrives.
In markets where supply tightens ahead of key milestones, price often begins to rise in anticipation. Mutuum Finance’s phase structure is designed around this window, with the later phases sitting closer to public launch levels.
Part of what makes Mutuum Finance stand out is how the protocol plans to create internal demand based on usage rather than attention. When users deposit assets into lending pools, they receive mtTokens.
These tokens represent their deposit positions and rise in value as interest flows into the pool. For example, a user who supplies 2,000 USDC receives equivalent mtUSDC. As borrowing demand increases, interest flows to these mtUSDC holders as APY. This ties price and demand to real lending flow rather than social chatter.
Another source of demand comes from the buy-and-distribute model. A portion of protocol revenue is used to buy MUTM on the open market. Those purchased tokens are then redistributed to users who stake mtTokens in the protocol’s safety module. This creates a feedback loop driven by revenue.
When usage rises, more revenue flows into the buy-and-distribute system. That creates buy pressure that is tied to usage rather than headlines or narrative alone. This contrasts with many new crypto assets that depend on hype or short-term attention spikes. Mutuum Finance links demand to activity that has financial meaning when it goes live.
First, security preparation has been completed. The protocol finished an independent audit with Halborn Security, a firm known for reviewing complex DeFi codebases. It also received a 90/100 Token Scan score from CertiK and launched a $50,000 bug bounty to encourage testing before final deployment.
Second, participation features like the 24-hour leaderboard keep engagement high. The leaderboard rewards the top daily contributor with $500 in MUTM. This encourages consistent activity rather than sudden bursts, and it keeps liquidity flowing through the distribution phases.
Third, the presale supports card payments in addition to traditional crypto methods. This broadens accessibility and helps attract users who might not otherwise participate before utility arrives.
All of these signals sit under the surface of the next major step: V1 deployment on Ethereum’s Sepolia testnet and subsequent mainnet release. Once that happens, real borrowing and lending events will begin. At that point, usage data — not just expectations — will be available for markets to judge value creation.
This is why many market watchers refer to this as a pre-utility pricing window. In such windows, price reflects the expectation of future utility rather than the utility itself. For tokens tied to real revenue engines like Mutuum Finance, this shift from concept to execution is often where breakout moves begin.
For more information about Mutuum Finance (MUTM) visit the links below:
Website: https://www.mutuum.com
:::tip This story was published as a press release by Btcwire under HackerNoon’s Business Blogging Program. Do Your Own Research before making any financial decision.
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